Book

LabelDP-Pro: Learning with Label Differential Privacy via Projections Badih Ghazi, Yangsibo Huang, Pritish Kamath, Ravi Kumar, Pasin Manurangsi, Chiyuan Zhang

Implicit Maximum a Posteriori Filtering via Adaptive Optimization Gianluca Bencomo, Jake Snell, Thomas L. Griffiths

The Unreasonable Effectiveness of Linear Prediction as a Perceptual Metric Daniel Severo, Lucas Theis, Johannes Ballé

Batch Calibration: Rethinking Calibration for In-Context Learning and Prompt Engineering Han Zhou, Xingchen Wan, Lev Proleev, Diana Mincu, Jilin Chen, Katherine Heller, Subhrajit Roy

LLM Augmented LLMs: Expanding Capabilities through Composition Rachit Bansal, Bidisha Samanta, Siddharth Dalmia, Nitish Gupta, Sriram Ganapathy, Abhishek Bapna, Prateek Jain, Partha Talukdar

SEA: Sparse Linear Attention with Estimated Attention Mask Heejun Lee, Jina Kim, Jeff Willette, Sung Ju Hwang

Towards Understanding Sycophancy in Language Models Mrinank Sharma, Meg Tong, Tomek Korbak, David Duvenaud, Amanda Askell, Sam Bowman, Esin DURMUS, Zac Hatfield-Dodds, Scott Johnston, Shauna Kravec, Timothy Maxwell, Sam McCandlish, Kamal Ndousse, Oliver Rausch, Nicholas Schiefer, Da Yan, Miranda Zhang, Ethan Perez

Entropy Coding of Unordered Data Structures Julius Kunze, Daniel Severo, giulio zani, Jan-Willem van de Meent, James Townsend

Nemesis: Normalizing the Soft-prompt Vectors of Vision-Language Models Shuai Fu, Xiequn Wang, Qiushi Huang, Yu Zhang

What does the Knowledge Neuron Thesis Have to do with Knowledge? Jingcheng Niu, Andrew Liu, Zining Zhu, Gerald Penn

Robust NAS under adversarial training: benchmark, theory, and beyond Yongtao Wu, Fanghui Liu, Carl-Johann Simon-Gabriel, Grigorios Chrysos, Volkan Cevher

Dynamic Sparse No Training: Training-Free Fine-tuning for Sparse LLMs Yuxin Zhang, Lirui Zhao, Mingbao Lin, Sun Yunyun, Yiwu Yao, Xingjia Han, Jared Tanner, Shiwei Liu, Rongrong Ji

Mirage: Model-agnostic Graph Distillation for Graph Classification Mridul Gupta, Sahil Manchanda, HARIPRASAD KODAMANA, Sayan Ranu

Influencer Backdoor Attack on Semantic Segmentation Haoheng Lan, Jindong Gu, Philip Torr, Hengshuang Zhao

A Newborn Embodied Turing Test for Comparing Object Segmentation Across Animals and Machines Manju Garimella, Denizhan Pak, Justin Wood, Samantha Wood

The Expressive Leaky Memory Neuron: an Efficient and Expressive Phenomenological Neuron Model Can Solve Long-Horizon Tasks. Aaron Spieler, Nasim Rahaman, Georg Martius, David Ha, Anna Levina

Latent 3D Graph Diffusion Yuning You, Ruida Zhou, Jiwoong Park, Haotian Xu, Chao Tian, Zhangyang Wang, Yang Shen

Unbalancedness in Neural Monge Maps Improves Unpaired Domain Translation Luca Eyring, Dominik Klein, Théo Uscidda, Giovanni Palla, Niki Kilbertus, Zeynep Akata, Fabian Theis

Score Models for Offline Goal-Conditioned Reinforcement Learning Harshit Sikchi, Rohan Chitnis, Ahmed Touati, Alborz Geramifard, Amy Zhang, Scott Niekum

It's Never Too Late: Fusing Acoustic Information into Large Language Models for Automatic Speech Recognition CHEN CHEN, Ruizhe Li, Yuchen Hu, Sabato Siniscalchi, Pin-Yu Chen, Ensiong Chng, Chao-Han Huck Yang

Rethinking Information-theoretic Generalization: Loss Entropy Induced PAC Bounds Yuxin Dong, Tieliang Gong, Hong Chen, Shujian Yu, Chen Li

Finite-Time Analysis of On-Policy Heterogeneous Federated Reinforcement Learning Chenyu Zhang, Han Wang, Aritra Mitra, James Anderson

Decentralized Riemannian Conjugate Gradient Method on the Stiefel Manifold Jun Chen, Haishan Ye, Mengmeng Wang, Tianxin Huang, Guang Dai, Ivor Tsang, Yong Liu

BrainLM: A foundation model for brain activity recordings Josue Ortega Caro, Antonio Henrique de Oliveira Fonseca, Syed Rizvi, Matteo Rosati, Christopher Averill, James Cross, Prateek Mittal, Emanuele Zappala, Rahul Dhodapkar, Chadi Abdallah, David van Dijk

Branch-GAN: Improving Text Generation with (not so) Large Language Models Fredrik Carlsson, Johan Broberg, Erik Hillbom, Magnus Sahlgren, Joakim Nivre

Maximum Entropy Model Correction in Reinforcement Learning Amin Rakhsha, Mete Kemertas, Mohammad Ghavamzadeh, Amir-massoud Farahmand

Does Writing with Language Models Reduce Content Diversity? Vishakh Padmakumar, He He

Modulate Your Spectrum in Self-Supervised Learning Xi Weng, Yunhao Ni, Tengwei Song, Jie Luo, Rao Anwer, Salman Khan, Fahad Khan, Lei Huang

NaturalSpeech 2: Latent Diffusion Models are Natural and Zero-Shot Speech and Singing Synthesizers Kai Shen, Zeqian Ju, Xu Tan, Eric Liu, Yichong Leng, Lei He, Tao Qin, sheng zhao, Jiang Bian

Context is Environment Sharut Gupta, Stefanie Jegelka, David Lopez-Paz, Kartik Ahuja

Language Model Beats Diffusion - Tokenizer is key to visual generation Lijun Yu, José Lezama, Nitesh Bharadwaj Gundavarapu, Luca Versari, Kihyuk Sohn, David Minnen, Yong Cheng, Agrim Gupta, Xiuye Gu, Alexander G Hauptmann, Boqing Gong, Ming-Hsuan Yang, Irfan Essa, David Ross, Lu Jiang

Evaluating Language Model Agency Through Negotiations Tim R. Davidson, Veniamin Veselovsky, Michal Kosinski, Robert West

Duolando: Follower GPT with Off-Policy Reinforcement Learning for Dance Accompaniment Siyao Li, Tianpei Gu, Zhitao Yang, Zhengyu Lin, Ziwei Liu, Henghui Ding, Lei Yang, Chen Change Loy

Object centric architectures enable efficient causal representation learning Amin Mansouri, Jason Hartford, Yan Zhang, Yoshua Bengio

A Lightweight Method for Tackling Unknown Participation Statistics in Federated Averaging Shiqiang Wang, Mingyue Ji

Frozen Transformers in Language Models Are Effective Visual Encoder Layers Ziqi Pang, Ziyang Xie, Yunze Man, Yu-Xiong Wang

Skeleton-of-Thought: Prompting LLMs for Efficient Parallel Generation Xuefei Ning, Zinan Lin, Zixuan Zhou, Zifu Wang, Huazhong Yang, Yu Wang

Image Inpainting via Tractable Steering of Diffusion Models Anji Liu, Mathias Niepert, Guy Van den Broeck

Ito Diffusion Approximation of Universal Ito Chains for Sampling, Optimization and Boosting Aleksei Ustimenko, Aleksandr Beznosikov

On the generalization capacity of neural networks during generic multimodal reasoning Takuya Ito, Soham Dan, Mattia Rigotti, James Kozloski, Murray Campbell

Convolutional Deep Kernel Machines Edward Milsom, Ben Anson, Laurence Aitchison

Mind Your Augmentation: The Key to Decoupling Dense Self-Supervised Learning Congpei Qiu, Tong Zhang, Yanhao Wu, Wei Ke, Mathieu Salzmann, Sabine Susstrunk

Course Correcting Koopman Representations Mahan Fathi, Clement Gehring, Jonathan Pilault, David Kanaa, Pierre-Luc Bacon, Ross Goroshin

Generalized Policy Iteration using Tensor Approximation for Hybrid Control Suhan Shetty, Teng Xue, Sylvain Calinon

Retrieval-Enhanced Contrastive Vision-Text Models Ahmet Iscen, Mathilde Caron, Alireza Fathi, Cordelia Schmid

Sample Efficient Myopic Exploration Through Multitask Reinforcement Learning with Diverse Tasks Ziping Xu, Zifan Xu, Runxuan Jiang, Peter Stone, Ambuj Tewari

Circumventing Concept Erasure Methods For Text-To-Image Generative Models Minh Pham, Kelly Marshall, Niv Cohen, Govind Mittal, Chinmay Hegde

NECO: NEural Collapse Based Out-of-distribution detection Mouïn Ben Ammar, Nacim Belkhir, Sebastian Popescu, Antoine Manzanera, Gianni Franchi

"What Data Benefits My Classifier?" Enhancing Model Performance and Interpretability through Influence-Based Data Selection Anshuman Chhabra, Peizhao Li, Prasant Mohapatra, Hongfu Liu

COCO-Periph: Bridging the Gap Between Human and Machine Perception in the Periphery Anne Harrington, Vasha DuTell, Mark Hamilton, Ayush Tewari, Simon Stent, William Freeman, Ruth Rosenholtz

Doubly Robust Instance-Reweighted Adversarial Training Daouda Sow, Sen Lin, Zhangyang Wang, Yingbin Liang

OpenTab: Advancing Large Language Models as Open-domain Table Reasoners Kezhi Kong, Jiani Zhang, Zhengyuan Shen, Balasubramaniam Srinivasan, Chuan Lei, Christos Faloutsos, Huzefa Rangwala, George Karypis

Approximately Piecewise E(3) Equivariant Point Networks Matan Atzmon, Jiahui Huang, Francis Williams, Or Litany

BrainSCUBA: Fine-Grained Natural Language Captions of Visual Cortex Selectivity Andrew Luo, Maggie Henderson, Michael Tarr, Leila Wehbe

Debiasing Algorithm through Model Adaptation Tomasz Limisiewicz, David Mareček, Tomáš Musil

Image Clustering Conditioned on Text Criteria Sehyun Kwon, Jaden Park, Minkyu Kim, Jaewoong Cho, Ernest K. Ryu, Kangwook Lee

Fast Updating Truncated SVD for Representation Learning with Sparse Matrices Haoran Deng, Yang Yang, Jiahe Li, Cheng Chen, Weihao Jiang, Shiliang Pu

Phenomenal Yet Puzzling: Testing Inductive Reasoning Capabilities of Language Models with Hypothesis Refinement Linlu Qiu, Liwei Jiang, Ximing Lu, Melanie Sclar, Valentina Pyatkin, Chandra Bhagavatula, Bailin Wang, Yoon Kim, Yejin Choi, Nouha Dziri, Xiang Ren

Zero-Shot Continuous Prompt Transfer: Generalizing Task Semantics Across Language Models Zijun Wu, Yongkang Wu, Lili Mou

MaGIC: Multi-modality Guided Image Completion Hao Wang, Yongsheng Yu, Tiejian Luo, Heng Fan, Libo Zhang

Learning from Aggregate responses: Instance Level versus Bag Level Loss Functions Adel Javanmard, Lin Chen, Vahab Mirrokni, Ashwinkumar Badanidiyuru, Gang Fu

SmartPlay : A Benchmark for LLMs as Intelligent Agents Yue Wu, Xuan Tang, Tom Mitchell, Yuanzhi Li

Improved Regret Bounds for Non-Convex Online-Within-Online Meta Learning Jiechao GUAN, Hui Xiong

Hierarchical Context Merging: Better Long Context Understanding for Pre-trained LLMs Woomin Song, Seunghyuk Oh, Sangwoo Mo, Jaehyung Kim, Sukmin Yun, Jung-Woo Ha, Jinwoo Shin

TokenFlow: Consistent Diffusion Features for Consistent Video Editing Michal Geyer, Omer Bar Tal, Shai Bagon, Tali Dekel

Sophia: A Scalable Stochastic Second-order Optimizer for Language Model Pre-training Hong Liu, Zhiyuan Li, David Hall, Percy Liang, Tengyu Ma

Towards Best Practices of Activation Patching in Language Models: Metrics and Methods Fred Zhang, Neel Nanda

Smooth ECE: Principled Reliability Diagrams via Kernel Smoothing Jaroslaw Blasiok, Preetum Nakkiran

LaneSegNet: Map Learning with Lane Segment Perception for Autonomous Driving Tianyu Li, Peijin Jia, Bangjun Wang, Li Chen, Kun Jiang, Junchi Yan, Hongyang Li

A Discretization Framework for Robust Contextual Stochastic Optimization Rares Cristian, Georgia Perakis

Geographic Location Encoding with Spherical Harmonics and Sinusoidal Representation Networks Marc Rußwurm, Konstantin Klemmer, Esther Rolf, Robin Zbinden, Devis Tuia

ADOPD: A Large-Scale Document Page Decomposition Dataset Jiuxiang Gu, Xiangxi Shi, Jason Kuen, Lu Qi, Ruiyi Zhang, Anqi Liu, Ani Nenkova, Tong Sun

TorchRL: A data-driven decision-making library for PyTorch Albert Bou, Matteo Bettini, Sebastian Dittert, Vikash Kumar, Shagun Sodhani, Xiaomeng Yang, Gianni De Fabritiis, Vincent Moens

Bayesian Low-rank Adaptation for Large Language Models Adam Yang, Maxime Robeyns, Xi Wang, Laurence Aitchison

Never Train from Scratch: Fair Comparison of Long-Sequence Models Requires Data-Driven Priors Ido Amos, Jonathan Berant, Ankit Gupta

SDXL: Improving Latent Diffusion Models for High-Resolution Image Synthesis Dustin Podell, Zion English, Kyle Lacey, Andreas Blattmann, Tim Dockhorn, Jonas Müller, Joe Penna, Robin Rombach

Solving Homogeneous and Heterogeneous Cooperative Tasks with Greedy Sequential Execution Shanqi Liu, Dong Xing, Pengjie Gu, Xinrun Wang, Bo An, Yong Liu

Can LLMs Keep a Secret? Testing Privacy Implications of Language Models via Contextual Integrity Theory Niloofar Mireshghallah, Hyunwoo Kim, Xuhui Zhou, Yulia Tsvetkov, Maarten Sap, Reza Shokri, Yejin Choi

BECLR: Batch Enhanced Contrastive Few-Shot Learning Stylianos Poulakakis-Daktylidis, Hadi J. Rad

On Accelerating Diffusion-Based Sampling Processes via Improved Integration Approximation Guoqiang Zhang, Kenta Niwa, W. Bastiaan Kleijn

VersVideo: Leveraging Enhanced Temporal Diffusion Models for Versatile Video Generation Jinxi Xiang, Ricong Huang, Jun Zhang, Guanbin Li, Xiao Han, Yang Wei

Internal Cross-layer Gradients for Extending Homogeneity to Heterogeneity in Federated Learning Yun-Hin Chan, Rui Zhou, Running Zhao, Zhihan JIANG, Edith Ngai

GENOME: Generative Neuro-Symbolic Visual Reasoning by Growing and Reusing Modules Zhenfang Chen, Rui Sun, Wenjun Liu, Yining Hong, Chuang Gan

Compositional Conservatism: A Transductive Approach in Offline Reinforcement Learning Yeda Song, Dongwook Lee, Gunhee Kim

IMPUS: Image Morphing with Perceptually-Uniform Sampling Using Diffusion Models Zhaoyuan Yang, Zhengyang Yu, Zhiwei Xu, Jaskirat Singh, Jing Zhang, Dylan Campbell, Peter Tu, Richard Hartley

Sliced Wasserstein Estimation with Control Variates Khai Nguyen, Nhat Ho

GAIA: Zero-shot Talking Avatar Generation Tianyu He, Junliang Guo, Runyi Yu, Yuchi Wang, jialiang zhu, Kaikai An, Leyi Li, Xu Tan, Chunyu Wang, Han Hu, HsiangTao Wu, sheng zhao, Jiang Bian

Feature-aligned N-BEATS with Sinkhorn divergence Joonhun Lee, Myeongho Jeon, Myungjoo Kang, Kyunghyun Park

A Foundation Model for Error Correction Codes Yoni Choukroun, Lior Wolf

MuSc: Zero-Shot Industrial Anomaly Classification and Segmentation with Mutual Scoring of the Unlabeled Images Xurui Li, Ziming Huang, Feng Xue, Yu Zhou

Hypergraph Dynamic System Jielong Yan, Yifan Feng, Shihui Ying, Yue Gao

BaDExpert: Extracting Backdoor Functionality for Accurate Backdoor Input Detection Tinghao Xie, Xiangyu Qi, Ping He, Yiming Li, Jiachen (Tianhao) Wang, Prateek Mittal

Realistic Evaluation of Semi-supervised Learning Algorithms in Open Environments Lin-Han Jia, Lan-Zhe Guo, Zhi Zhou, Yu-Feng Li

Disentangling Time Series Representations via Contrastive Independence-of-Support on l-Variational Inference Khalid OUBLAL, Said Ladjal, David Benhaiem, Emmanuel LE BORGNE, François Roueff

ASMR: Activation-Sharing Multi-Resolution Coordinate Networks for Efficient Inference Jason Chun Lok Li, Steven Luo, Le Xu, Ngai Wong

Mastering Memory Tasks with World Models Mohammad Reza Samsami, Artem Zholus, Janarthanan Rajendran, Sarath Chandar

Are Bert Family Good Instruction Followers? A Study on Their Potential And Limitations yisheng xiao, Juntao Li, Zechen Sun, Zechang Li, Qingrong Xia, Xinyu Duan, Zhefeng Wang, Min Zhang

Reward-Free Curricula for Training Robust World Models Marc Rigter, Minqi Jiang, Ingmar Posner

Out-of-Distribution Detection by Leveraging Between-Layer Transformation Smoothness Fran Jelenić, Josip Jukić, Martin Tutek, Mate Puljiz, Jan Snajder

Gene Regulatory Network Inference in the Presence of Dropouts: a Causal View Haoyue Dai, Ignavier Ng, Gongxu Luo, Peter Spirtes, Petar Stojanov, Kun Zhang

Recursive Generalization Transformer for Image Super-Resolution Zheng Chen, Yulun Zhang, Jinjin Gu, Linghe Kong, Xiaokang Yang

Efficient Inverse Multiagent Learning Denizalp Goktas, Amy Greenwald, Sadie Zhao, Alec Koppel, Sumitra Ganesh

Language Models Represent Space and Time Wes Gurnee, Max Tegmark

Customizable Combination of Parameter-Efficient Modules for Multi-Task Learning Haowen Wang, Tao Sun, Congyun Jin, Yingbo Wang, Yibo Fan, Yunqi Xu, Yuliang Du, Cong Fan

Towards Category Unification of 3D Single Object Tracking on Point Clouds Jiahao Nie, Zhiwei He, Xudong Lv, Xueyi Zhou, Dong-Kyu Chae, Fei Xie

Don't Trust: Verify -- Grounding LLM Quantitative Reasoning with Autoformalization Jin Zhou, Charles Staats, Wenda Li, Christian Szegedy, Kilian Weinberger, Yuhuai Wu

Complete and Efficient Graph Transformers for Crystal Material Property Prediction Keqiang Yan, Cong Fu, Xiaofeng Qian, Xiaoning Qian, Shuiwang Ji

In-context Autoencoder for Context Compression in a Large Language Model Tao Ge, Hu Jing, Lei Wang, Xun Wang, Si-Qing Chen, Furu Wei

Privileged Sensing Scaffolds Reinforcement Learning Edward Hu, James Springer, Oleh Rybkin, Dinesh Jayaraman

Vision Transformers Need Registers Timothée Darcet, Maxime Oquab, Julien Mairal, Piotr Bojanowski

AdjointDPM: Adjoint Sensitivity Method for Gradient Backpropagation of Diffusion Probabilistic Models Jiachun Pan, Jun Hao Liew, Vincent Tan, Jiashi Feng, Hanshu Yan

Predictive auxiliary objectives in deep RL mimic learning in the brain Ching Fang, Kimberly Stachenfeld

Meta Continual Learning Revisited: Implicitly Enhancing Online Hessian Approximation via Variance Reduction Yichen Wu, Long-Kai Huang, Renzhen Wang, Deyu Meng, Ying Wei

Expressive Losses for Verified Robustness via Convex Combinations Alessandro De Palma, Rudy R Bunel, Krishnamurthy Dvijotham, M. Pawan Kumar, Robert Stanforth, Alessio Lomuscio

A Paradigm Shift in Machine Translation: Boosting Translation Performance of Large Language Models Haoran Xu, Young Jin Kim, Amr Mohamed Nabil Aly Aly Sharaf, Hany Awadalla

Delphic Offline Reinforcement Learning under Nonidentifiable Hidden Confounding Alizée Pace, Hugo Yèche, David Ha, Gunnar Ratsch, Guy Tennenholtz

Optimistic Bayesian Optimization with Unknown Constraints Quoc Phong Nguyen, Wan Theng Ruth Chew, Le Song, Bryan Kian Hsiang Low, Patrick Jaillet

Generalization error of spectral algorithms Maksim Velikanov, Maxim Panov, Dmitry Yarotsky

3D Reconstruction with Generalizable Neural Fields using Scene Priors Yang Fu, Shalini De Mello, Xueting Li, Amey Kulkarni, Jan Kautz, Xiaolong Wang, Sifei Liu

Graph Parsing Networks Yunchong Song, Siyuan Huang, Xinbing Wang, Chenghu Zhou, Zhouhan Lin

An LLM can Fool Itself: A Prompt-Based Adversarial Attack Xilie Xu, Keyi Kong, Ning Liu, Lizhen Cui, Di Wang, Jingfeng Zhang, Mohan Kankanhalli

CausalTime: Realistically Generated Time-series for Benchmarking of Causal Discovery YUXIAO CHENG, Ziqian Wang, Tingxiong Xiao, Qin Zhong, Jinli Suo, Kunlun He

ImplicitSLIM and How it Improves Embedding-based Collaborative Filtering Ilya Shenbin, Sergey Nikolenko

Lemur: Integrating Large Language Models in Automated Program Verification Haoze Wu, Clark Barrett, Nina Narodytska

HypeBoy: Generative Self-Supervised Representation Learning on Hypergraphs Sunwoo Kim, Shinhwan Kang, Fanchen Bu, Soo Yong Lee, Jaemin Yoo, Kijung Shin

TESTAM: A Time-Enhanced Spatio-Temporal Attention Model with Mixture of Experts Hyunwook Lee, Sungahn Ko

Learning Stackable and Skippable LEGO Bricks for Efficient, Reconfigurable, and Variable-Resolution Diffusion Modeling Huangjie Zheng, Zhendong Wang, Jianbo Yuan, Guanghan Ning, Pengcheng He, Quanzeng You, Hongxia Yang, Mingyuan Zhou

INSIDE: LLMs' Internal States Retain the Power of Hallucination Detection Chao Chen, Kai Liu, Ze Chen, Yi Gu, Yue Wu, Mingyuan Tao, Zhihang Fu, Jieping Ye

Equivariant Matrix Function Neural Networks Ilyes Batatia, Lars Leon Schaaf, Gábor Csányi, Christoph Ortner, Felix Faber

Minimum width for universal approximation using ReLU networks on compact domain Namjun Kim, Chanho Min, Sejun Park

ZeroFlow: Scalable Scene Flow via Distillation Kyle Vedder, Neehar Peri, Nathaniel Chodosh, Ishan Khatri, ERIC EATON, Dinesh Jayaraman, Yang Liu, Deva Ramanan, James Hays

Enhanced Face Recognition using Intra-class Incoherence Constraint Yuanqing Huang, Yinggui Wang, Le Yang, Lei Wang

Large-scale Training of Foundation Models for Wearable Biosignals Salar Abbaspourazad, Oussama Elachqar, Andrew Miller, Saba Emrani, Udhyakumar Nallasamy, Ian Shapiro

Get What You Want, Not What You Don't: Image Content Suppression for Text-to-Image Diffusion Models Senmao Li, Joost van de Weijer, taihang Hu, Fahad Khan, Qibin Hou, Yaxing Wang, jian Yang

In-Context Learning Learns Label Relationships but Is Not Conventional Learning Jannik Kossen, Yarin Gal, Tom Rainforth

Continuous Field Reconstruction from Sparse Observations with Implicit Neural Networks Xihaier Luo, Wei Xu, Balasubramanya T. Nadiga, Yihui Ren, Shinjae Yoo

Generalization of Scaled Deep ResNets in the Mean-Field Regime Yihang Chen, Fanghui Liu, Yiping Lu, Grigorios Chrysos, Volkan Cevher

LEMON: Lossless model expansion Yite Wang, Jiahao Su, Hanlin Lu, Cong Xie, Tianyi Liu, Jianbo Yuan, Haibin Lin, Ruoyu Sun, Hongxia Yang

V-DETR: DETR with Vertex Relative Position Encoding for 3D Object Detection Yichao Shen, Zigang Geng, YUHUI YUAN, Yutong Lin, Ze Liu, Chunyu Wang, Han Hu, Nanning Zheng, Baining Guo

SequenceMatch: Imitation Learning for Autoregressive Sequence Modelling with Backtracking Chris Cundy, Stefano Ermon

Explaining Kernel Clustering via Decision Trees Maximilian Fleissner, Leena Chennuru Vankadara, Debarghya Ghoshdastidar

Early Neuron Alignment in Two-layer ReLU Networks with Small Initialization Hancheng Min, Enrique Mallada, Rene Vidal

Seer: Language Instructed Video Prediction with Latent Diffusion Models Xianfan Gu, Chuan Wen, Weirui Ye, Jiaming Song, Yang Gao

Neural Fine-Tuning Search for Few-Shot Learning Panagiotis Eustratiadis, Łukasz Dudziak, Da Li, Timothy Hospedales

Provable Benefits of Multi-task RL under Non-Markovian Decision Making Processes Ruiquan Huang, Yuan Cheng, Jing Yang, Vincent Tan, Yingbin Liang

Self-Alignment with Instruction Backtranslation Xian Li, Ping Yu, Chunting Zhou, Timo Schick, Omer Levy, Luke Zettlemoyer, Jason E Weston, Mike Lewis

Learning Planning Abstractions from Language Weiyu Liu, Geng Chen, Joy Hsu, Jiayuan Mao, Jiajun Wu

Test-Time Adaptation with CLIP Reward for Zero-Shot Generalization in Vision-Language Models Shuai Zhao, Xiaohan Wang, Linchao Zhu, Yi Yang

Statistical Perspective of Top-K Sparse Softmax Gating Mixture of Experts Huy Nguyen, Pedram Akbarian Saravi, Fanqi Yan, Nhat Ho

GeneOH Diffusion: Towards Generalizable Hand-Object Interaction Denoising via Denoising Diffusion Xueyi Liu, Li Yi

Free from Bellman Completeness: Trajectory Stitching via Model-based Return-conditioned Supervised Learning Zhaoyi Zhou, Chuning Zhu, Runlong Zhou, Qiwen Cui, Abhishek Gupta, Simon Du

Physics-Regulated Deep Reinforcement Learning: Invariant Embeddings Hongpeng Cao, Yanbing Mao, Lui Sha, Marco Caccamo

Demystifying Local & Global Fairness Trade-offs in Federated Learning Using Partial Information Decomposition Faisal Hamman, Sanghamitra Dutta

To Grok or not to Grok: Disentangling Generalization and Memorization on Corrupted Algorithmic Datasets Darshil Doshi, Aritra Das, Tianyu He, Andrey Gromov

GRANDE: Gradient-Based Decision Tree Ensembles for Tabular Data Sascha Marton, Stefan Lüdtke, Christian Bartelt, Heiner Stuckenschmidt

Safe Offline Reinforcement Learning with Feasibility-Guided Diffusion Model Yinan Zheng, Jianxiong Li, Dongjie Yu, Yujie Yang, Shengbo Li, Xianyuan Zhan, Jingjing Liu

Think-on-Graph: Deep and Responsible Reasoning of Large Language Model on Knowledge Graph Jiashuo Sun, Chengjin Xu, Lumingyuan Tang, Saizhuo Wang, Chen Lin, Yeyun Gong, Lionel Ni, Heung-Yeung Shum, Jian Guo

CALICO: Self-Supervised Camera-LiDAR Contrastive Pre-training for BEV Perception Jiachen Sun, Haizhong Zheng, Qingzhao Zhang, Atul Prakash, Zhuoqing Mao, Chaowei Xiao

Robust Adversarial Reinforcement Learning via Bounded Rationality Curricula Aryaman Reddi, Maximilian Tölle, Jan Peters, Georgia Chalvatzaki, Carlo D'Eramo

On Representation Complexity of Model-based and Model-free Reinforcement Learning Hanlin Zhu, Baihe Huang, Stuart Russell

Deceptive Fairness Attacks on Graphs via Meta Learning Jian Kang, Yinglong Xia, Ross Maciejewski, Jiebo Luo, Hanghang Tong

RingAttention with Blockwise Transformers for Near-Infinite Context Hao Liu, Matei Zaharia, Pieter Abbeel

DynaVol: Unsupervised Learning for Dynamic Scenes through Object-Centric Voxelization Yanpeng Zhao, Siyu Gao, Yunbo Wang, Xiaokang Yang

Confidential-DPproof: Confidential Proof of Differentially Private Training Ali Shahin Shamsabadi, Gefei Tan, Tudor Cebere, Aurélien Bellet, Hamed Haddadi, Nicolas Papernot, Xiao Wang, Adrian Weller

Prompt Risk Control: A Rigorous Framework for Responsible Deployment of Large Language Models Thomas Zollo, Todd Morrill, Zhun Deng, Jake Snell, Toniann Pitassi, Richard Zemel

Contextual Bandits with Online Neural Regression Rohan Deb, Yikun Ban, Shiliang Zuo, Jingrui He, Arindam Banerjee

Efficient Continual Finite-Sum Minimization Ioannis Mavrothalassitis, Stratis Skoulakis, Leello Dadi, Volkan Cevher

Language Model Cascades: Token-Level Uncertainty And Beyond Neha Gupta, Harikrishna Narasimhan, Wittawat Jitkrittum, Ankit Singh Rawat, Aditya Krishna Menon, Sanjiv Kumar

LogicMP: A Neuro-symbolic Approach for Encoding First-order Logic Constraints Weidi Xu, Jingwei Wang, Lele Xie, Jianshan He, Hongting Zhou, Taifeng Wang, Xiaopei Wan, Jingdong Chen, Chao Qu, Wei Chu

Understanding when Dynamics-Invariant Data Augmentations Benefit Model-free Reinforcement Learning Updates Nicholas Corrado, Josiah Hanna

REValueD: Regularised Ensemble Value-Decomposition for Factorisable Markov Decision Processes David Ireland, Giovanni Montana

Some Fundamental Aspects about Lipschitz Continuity of Neural Networks Grigory Khromov, Sidak Pal Singh

How to Capture Higher-order Correlations? Generalizing Matrix Softmax Attention to Kronecker Computation Josh Alman, Zhao Song

A Variational Framework for Estimating Continuous Treatment Effects with Measurement Error Erdun Gao, Howard Bondell, Wei Huang, Mingming Gong

Inner Classifier-Free Guidance and Its Taylor Expansion for Diffusion Models Shikun Sun, Longhui Wei, Zhicai Wang, Zixuan Wang, Junliang Xing, Jia Jia, Qi Tian

Pessimistic Nonlinear Least-Squares Value Iteration for Offline Reinforcement Learning Qiwei Di, Heyang Zhao, Jiafan He, Quanquan Gu

A Quadratic Synchronization Rule for Distributed Deep Learning Xinran Gu, Kaifeng Lyu, Sanjeev Arora, Jingzhao Zhang, Longbo Huang

Identifying Policy Gradient Subspaces Jan Schneider, Pierre Schumacher, Simon Guist, Le Chen, Daniel Haeufle, David Ha, Dieter Büchler

Solving Challenging Math Word Problems Using GPT-4 Code Interpreter with Code-based Self-Verification Aojun Zhou, Ke Wang, Zimu Lu, Weikang Shi, Sichun Luo, Zipeng Qin, Shaoqing Lu, Anya Jia, Linqi Song, Mingjie Zhan, Hongsheng Li

InstructDET: Diversifying Referring Object Detection with Generalized Instructions Ronghao Dang, Jiangyan Feng, Haodong Zhang, Chongjian GE, Lin Song, Lijun GONG, Chengju Liu, Qijun Chen, Feng Zhu, Rui Zhao, Yibing Song

ToolChain*: Efficient Action Space Navigation in Large Language Models with A* Search Yuchen Zhuang, Xiang Chen, Tong Yu, Saayan Mitra, Victor Bursztyn, Ryan Rossi, Somdeb Sarkhel, Chao Zhang

Better Neural PDE Solvers Through Data-Free Mesh Movers Peiyan Hu, Yue Wang, Zhi-Ming Ma

Tractable MCMC for Private Learning with Pure and Gaussian Differential Privacy Yingyu Lin, Yian Ma, Yu-Xiang Wang, Rachel Redberg, Zhiqi Bu

Correlated Noise Provably Beats Independent Noise for Differentially Private Learning Christopher Choquette-Choo, Krishnamurthy Dvijotham, Krishna Pillutla, Arun Ganesh, Thomas Steinke, Abhradeep Guha Thakurta

Symmetric Basis Convolutions for Learning Lagrangian Fluid Mechanics Rene Winchenbach, Nils Thuerey

Task Planning for Visual Room Rearrangement under Partial Observability Karan Mirakhor, Sourav Ghosh, DIPANJAN DAS, Brojeshwar Bhowmick

Learning Hierarchical World Models with Adaptive Temporal Abstractions from Discrete Latent Dynamics Christian Gumbsch, Noor Sajid, Georg Martius, Martin V. Butz

Directly Fine-Tuning Diffusion Models on Differentiable Rewards Kevin Clark, Paul Vicol, Kevin Swersky, David Fleet

MCM: Masked Cell Modeling for Anomaly Detection in Tabular Data Jiaxin Yin, Yuanyuan Qiao, Zitang Zhou, Xiangchao Wang, Jie Yang

Large Language Models are Efficient Learners of Noise-Robust Speech Recognition Yuchen Hu, CHEN CHEN, Chao-Han Huck Yang, Ruizhe Li, Chao Zhang, Pin-Yu Chen, Ensiong Chng

Scalable Modular Network: A Framework for Adaptive Learning via Agreement Routing Minyang Hu, Hong Chang, Bingpeng Ma, Shiguang Shan, Xilin CHEN

GenSim: Generating Robotic Simulation Tasks via Large Language Models Lirui Wang, Yiyang Ling, Zhecheng Yuan, Mohit Shridhar, Chen Bao, Yuzhe Qin, Bailin Wang, Huazhe Xu, Xiaolong Wang

A Progressive Training Framework for Spiking Neural Networks with Learnable Multi-hierarchical Model Zecheng Hao, Xinyu Shi, Zihan Huang, Tong Bu, Zhaofei Yu, Tiejun Huang

A Simple and Effective Pruning Approach for Large Language Models Mingjie Sun, Zhuang Liu, Anna Bair, Zico Kolter

Training Diffusion Models with Reinforcement Learning Kevin Black, Michael Janner, Yilun Du, Ilya Kostrikov, Sergey Levine

Near-Optimal Quantum Algorithm for Minimizing the Maximal Loss Hao Wang, Chenyi Zhang, Tongyang Li

MathCoder: Seamless Code Integration in LLMs for Enhanced Mathematical Reasoning Ke Wang, Houxing Ren, Aojun Zhou, Zimu Lu, Sichun Luo, Weikang Shi, Renrui Zhang, Linqi Song, Mingjie Zhan, Hongsheng Li

ValUES: A Framework for Systematic Validation of Uncertainty Estimation in Semantic Segmentation Kim-Celine Kahl, Carsten Lüth, Maximilian Zenk, Klaus Maier-Hein, Paul F. Jaeger

The Expressive Power of Low-Rank Adaptation Yuchen Zeng, Kangwook Lee

Revisiting Link Prediction: a data perspective Haitao Mao, Juanhui Li, Harry Shomer, Bingheng Li, Wenqi Fan, Yao Ma, Tong Zhao, Neil Shah, Jiliang Tang

Leveraging Hyperbolic Embeddings for Coarse-to-Fine Robot Design Heng Dong, Junyu Zhang, Chongjie Zhang

How connectivity structure shapes rich and lazy learning in neural circuits Yuhan Helena Liu, Aristide Baratin, Jonathan Cornford, Stefan Mihalas, Eric SheaBrown, Guillaume Lajoie

From Zero to Turbulence: Generative Modeling for 3D Flow Simulation Marten Lienen, David Lüdke, Jan Hansen-Palmus, Stephan Günnemann

Orbit-Equivariant Graph Neural Networks Matthew Morris, Bernardo Grau, Ian Horrocks

FreeNoise: Tuning-Free Longer Video Diffusion via Noise Rescheduling Haonan Qiu, Menghan Xia, Yong Zhang, Yingqing He, Xintao WANG, Ying Shan, Ziwei Liu

GraphChef: Decision-Tree Recipes to Explain Graph Neural Networks Peter Müller, Lukas Faber, Karolis Martinkus, Roger Wattenhofer

Window Attention is Bugged: How not to Interpolate Position Embeddings Daniel Bolya, Chaitanya Ryali, Judy Hoffman, Christoph Feichtenhofer

Don't Judge by the Look: Towards Motion Coherent Video Representation Yitian Zhang, Yue Bai, Huan Wang, Yizhou Wang, Yun Fu

Rethinking CNN’s Generalization to Backdoor Attack from Frequency Domain Quanrui Rao, Lin Wang, Wuying Liu

Estimating Shape Distances on Neural Representations with Limited Samples Dean Pospisil, Brett Larsen, Sarah Harvey, Alex Williams

Sheared LLaMA: Accelerating Language Model Pre-training via Structured Pruning Mengzhou Xia, Tianyu Gao, Zhiyuan Zeng, Danqi Chen

EMO: EARTH MOVER DISTANCE OPTIMIZATION FOR AUTO-REGRESSIVE LANGUAGE MODELING Siyu Ren, Zhiyong Wu, Kenny Zhu

Threshold-Consistent Margin Loss for Open-World Deep Metric Learning Qin ZHANG, Linghan Xu, Jun Fang, Qingming Tang, Yingnian Wu, Joseph Tighe, Yifan Xing

Beyond Accuracy: Evaluating Self-Consistency of Code Large Language Models with IdentityChain Marcus J. Min, Yangruibo Ding, Luca Buratti, Saurabh Pujar, Gail Kaiser, Suman Jana, Baishakhi Ray

Towards Foundational Models for Molecular Learning on Large-Scale Multi-Task Datasets Dominique Beaini, Shenyang(Andy) Huang, Joao Cunha, Zhiyi Li, Gabriela Moisescu-Pareja, Oleksandr Dymov, Samuel Maddrell-Mander, Callum McLean, Frederik Wenkel, Luis Müller, Jama Hussein Mohamud, Ali Parviz, Michael Craig, Michał Koziarski, Jiarui Lu, Zhaocheng Zhu, Cristian Gabellini, Kerstin Klaser, Josef Dean, Cas Wognum, Maciej Sypetkowski, Guillaume Rabusseau, Reihaneh Rabbany, Jian Tang, Christopher Morris, Mirco Ravanellu, Guy Wolf, Prudencio Tossou, Hadrien Mary, Therence Bois, Andrew Fitzgibbon, Blazej Banaszewski, Chad Martin, Dominic Masters

Backdoor Contrastive Learning via Bi-level Trigger Optimization Weiyu Sun, Xinyu Zhang, Hao LU, YINGCONG CHEN, Ting Wang, Jinghui Chen, Lu Lin

GROOT: Learning to Follow Instructions by Watching Gameplay Videos Shaofei Cai, Bowei Zhang, Zihao Wang, Xiaojian Ma, Anji Liu, Yitao Liang

PlaSma: Procedural Knowledge Models for Language-based Planning and Re-Planning Faeze Brahman, Chandra Bhagavatula, Valentina Pyatkin, Jena Hwang, Xiang Lorraine Li, Hirona Arai, Soumya Sanyal, Keisuke Sakaguchi, Xiang Ren, Yejin Choi

DiffusionSat: A Generative Foundation Model for Satellite Imagery Samar Khanna, Patrick Liu, Linqi Zhou, Chenlin Meng, Robin Rombach, Marshall Burke, David Lobell, Stefano Ermon

DiffusionNAG: Predictor-guided Neural Architecture Generation with Diffusion Models Sohyun An, Hayeon Lee, Jaehyeong Jo, Seanie Lee, Sung Ju Hwang

Mediator Interpretation and Faster Learning Algorithms for Linear Correlated Equilibria in General Sequential Games Brian Zhang, Gabriele Farina, Tuomas Sandholm

CellPLM: Pre-training of Cell Language Model Beyond Single Cells Hongzhi Wen, Wenzhuo Tang, Xinnan Dai, Jiayuan Ding, Wei Jin, Yuying Xie, Jiliang Tang

ODE Discovery for Longitudinal Heterogeneous Treatment Effects Inference Krzysztof Kacprzyk, Samuel Holt, Jeroen Berrevoets, Zhaozhi Qian, Mihaela van der Schaar

Harnessing Explanations: LLM-to-LM Interpreter for Enhanced Text-Attributed Graph Representation Learning Xiaoxin He, Xavier Bresson, Thomas Laurent, Adam Perold, Yann LeCun, Bryan Hooi

SpQR: A Sparse-Quantized Representation for Near-Lossless LLM Weight Compression Tim Dettmers, Ruslan Svirschevski, Vage Egiazarian, Denis Kuznedelev, Elias Frantar, Saleh Ashkboos, Alexander Borzunov, Torsten Hoefler, Dan Alistarh

HIFA: High-fidelity Text-to-3D Generation with Advanced Diffusion Guidance Junzhe Zhu, Peiye Zhuang, Sanmi Koyejo

RobustTSF: Towards Theory and Design of Robust Time Series Forecasting with Anomalies Hao Cheng, Qingsong Wen, Yang Liu, Liang Sun

Towards Eliminating Hard Label Constraints in Gradient Inversion Attacks Yanbo Wang, Jian Liang, Ran He

The Consensus Game: Language Model Generation via Equilibrium Search Athul Jacob, Yikang Shen, Gabriele Farina, Jacob Andreas

Follow-Up Differential Descriptions: Language Models Resolve Ambiguities for Image Classification Reza Esfandiarpoor, Stephen Bach

Batch normalization is sufficient for universal function approximation in CNNs Rebekka Burkholz

DecompOpt: Controllable and Decomposed Diffusion Models for Structure-based Molecular Optimization Xiangxin Zhou, Xiwei Cheng, Yuwei Yang, Yu Bao, Liang Wang, Quanquan Gu

A Unified Framework for Bayesian Optimization under Contextual Uncertainty Sebastian Shenghong Tay, Chuan Sheng Foo, Daisuke Urano, Richalynn Leong, Bryan Kian Hsiang Low

CLAP: Collaborative Adaptation for Patchwork Learning Sen Cui, Abudukelimu Wuerkaixi, Weishen Pan, Jian Liang, Lei Fang, Changshui Zhang, Fei Wang

Diffusion Sampling with Momentum for Mitigating Divergence Artifacts Suttisak Wisadwongsa, Worameth Chinchuthakun, Pramook Khungurn, Amit Raj, Supasorn Suwajanakorn

Raidar: geneRative AI Detection viA Rewriting Chengzhi Mao, Carl Vondrick, Hao Wang, Junfeng Yang

When Do Prompting and Prefix-Tuning Work? A Theory of Capabilities and Limitations Aleksandar Petrov, Philip Torr, Adel Bibi

ALAM: Averaged Low-Precision Activation for Memory-Efficient Training of Transformer Models Sunghyeon Woo, SunWoo Lee, Dongsuk Jeon

OMNI: Open-endedness via Models of human Notions of Interestingness Jenny Zhang, Joel Lehman, Kenneth Stanley, Jeff Clune

Transformer-VQ: Linear-Time Transformers via Vector Quantization Lucas D. Lingle

SaNN: Simple Yet Powerful Simplicial-aware Neural Networks Sravanthi Gurugubelli, Sundeep Prabhakar Chepuri

RETSim: Resilient and Efficient Text Similarity Marina Zhang, Owen Vallis, Aysegul Bumin, Tanay Vakharia, Elie Bursztein

Enabling Lanuguage Models to Implicitly Learn Self-Improvement Ziqi Wang, Le Hou, Tianjian Lu, Yuexin Wu, Yunxuan Li, Hongkun Yu, Heng Ji

Are Human-generated Demonstrations Necessary for In-context Learning? Rui Li, Guoyin Wang, Jiwei Li

Tag2Text: Guiding Vision-Language Model via Image Tagging Xinyu Huang, Youcai Zhang, Jinyu Ma, Weiwei Tian, Rui Feng, Yuejie Zhang, Yaqian Li, Yandong Guo, Lei Zhang

The Curse of Diversity in Ensemble-Based Exploration Zhixuan Lin, Pierluca D'Oro, Evgenii Nikishin, Aaron Courville

CABINET: Content Relevance-based Noise Reduction for Table Question Answering Sohan Patnaik, Heril Changwal, Milan Aggarwal, Sumit Bhatia, Yaman Singla, Balaji Krishnamurthy

Multi-Task Reinforcement Learning with Mixture of Orthogonal Experts Ahmed Hendawy, Jan Peters, Carlo D'Eramo

EventRPG: Event Data Augmentation with Relevance Propagation Guidance Mingyuan Sun, Donghao Zhang, Zongyuan Ge, Jiaxu Wang, Jia Li, Zheng Fang, Renjing Xu

Enhancing One-Shot Federated Learning Through Data and Ensemble Co-Boosting Rong Dai, Yonggang Zhang, Ang Li, Tongliang Liu, Xun Yang, Bo Han

From Posterior Sampling to Meaningful Diversity in Image Restoration Noa Cohen, Hila Manor, Yuval Bahat, Tomer Michaeli

Provable Reward-Agnostic Preference-Based Reinforcement Learning Wenhao Zhan, Masatoshi Uehara, Wen Sun, Jason Lee

The Devil is in the Neurons: Interpreting and Mitigating Social Biases in Language Models Yan Liu, Yu Liu, Xiaokang Chen, Pin-Yu Chen, Daoguang Zan, Min-Yen Kan, Tsung-Yi Ho

Consistency-guided Prompt Learning for Vision-Language Models Shuvendu Roy, Ali Etemad

A Semantic Invariant Robust Watermark for Large Language Models Aiwei Liu, Leyi Pan, Xuming Hu, Shiao Meng, Lijie Wen

Non-negative Contrastive Learning Yifei Wang, Qi Zhang, Yaoyu Guo, Yisen Wang

Towards Cross Domain Generalization of Hamiltonian Representation via Meta Learning Yeongwoo Song, Hawoong Jeong

A Differentially Private Clustering Algorithm for Well-Clustered Graphs Weiqiang He, Hendrik Fichtenberger, Pan Peng

Illusory Attacks: Information-theoretic detectability matters in adversarial attacks Tim Franzmeyer, Stephen McAleer, Joao F. Henriques, Jakob Foerster, Philip Torr, Adel Bibi, Christian Schroeder de Witt

Perceptual Group Tokenizer: Building Perception with Iterative Grouping Zhiwei Deng, Ting Chen, Yang Li

When can transformers reason with abstract symbols? Enric Boix-Adserà, Omid Saremi, Emmanuel Abbe, Samy Bengio, Etai Littwin, Joshua Susskind

DreamLLM: Synergistic Multimodal Comprehension and Creation Runpei Dong, chunrui han, Yuang Peng, Zekun Qi, Zheng Ge, Jinrong Yang, Liang Zhao, Jianjian Sun, Hongyu Zhou, Haoran Wei, Xiangwen Kong, Xiangyu Zhang, Kaisheng Ma, Li Yi

Fast, Expressive $\mathrm{SE}(n)$ Equivariant Networks through Weight-Sharing in Position-Orientation Space Erik Bekkers, Sharvaree Vadgama, Rob Hesselink, Putri van der Linden, David Wilson Romero

Neural Fourier Transform: A General Approach to Equivariant Representation Learning Masanori Koyama, Kenji Fukumizu, Kohei Hayashi, Takeru Miyato

Classification with Conceptual Safeguards Hailey Joren, Charles Marx, Berk Ustun

Soft Mixture Denoising: Beyond the Expressive Bottleneck of Diffusion Models Yangming Li, Boris van Breugel, Mihaela van der Schaar

Self-supervised Representation Learning from Random Data Projectors Yi Sui, Tongzi Wu, Jesse Cresswell, Ga Wu, George Stein, Xiao Shi (Gary) Huang, Xiaochen Zhang, Maksims Volkovs

VeRA: Vector-based Random Matrix Adaptation Dawid Kopiczko, Tijmen Blankevoort, Yuki Asano

Space Group Constrained Crystal Generation Rui Jiao, Wenbing Huang, Yu Liu, Deli Zhao, Yang Liu

LCOT: Linear Circular Optimal Transport ROCIO DIAZ MARTIN, Ivan Medri, Yikun Bai, Xinran Liu, Kangbai Yan, Gustavo Rohde, Soheil Kolouri

Cleanba: A Reproducible and Efficient Distributed Reinforcement Learning Platform Shengyi Huang, Jiayi Weng, Rujikorn Charakorn, Min Lin, Zhongwen Xu, Santiago Ontanon

TAB: Temporal Accumulated Batch Normalization in Spiking Neural Networks Haiyan Jiang, Vincent Zoonekynd, Giulia De Masi, Bin Gu, Huan Xiong

Adaptive Stochastic Gradient Algorithm for Black-box Multi-Objective Learning Feiyang YE, YUEMING LYU, Xuehao Wang, Yu Zhang, Ivor Tsang

Energy-Based Concept Bottleneck Models: Unifying Prediction, Concept Intervention, and Probabilistic Interpretations Xinyue Xu, Yi Qin, Lu Mi, Hao Wang, Xiaomeng Li

Offline RL with Observation Histories: Analyzing and Improving Sample Complexity Joey Hong, Anca Dragan, Sergey Levine

SaProt: Protein Language Modeling with Structure-aware Vocabulary Jin Su, Chenchen Han, Yuyang Zhou, Junjie Shan, Xibin Zhou, Fajie Yuan

AUC-CL: A Batchsize-Robust Framework for Self-Supervised Contrastive Representation Learning Rohan Sharma, Kaiyi Ji, Zhiqiang Xu, Changyou Chen

Let's do the time-warp-attend: Learning topological invariants of dynamical systems Noa Moriel, Matthew Ricci, Mor Nitzan

Fake It Till Make It: Federated Learning with Consensus-Oriented Generation Rui Ye, Yaxin Du, Zhenyang Ni, Yanfeng Wang, Siheng Chen

DV-3DLane: End-to-end Multi-modal 3D Lane Detection with Dual-view Representation Yueru Luo, Shuguang Cui, Zhen Li

Oracle Efficient Algorithms for Groupwise Regret Krishna Acharya, Eshwar Ram Arunachaleswaran, Sampath Kannan, Aaron Roth, Juba Ziani

Enhancing Neural Subset Selection: Integrating Background Information into Set Representations Binghui Xie, Yatao Bian, Kaiwen Zhou, Yongqiang Chen, Peilin Zhao, Bo Han, Wei Meng, James Cheng

Robust Classification via Regression for Learning with Noisy Labels Erik Englesson, Hossein Azizpour

DIFFTACTILE: A Physics-based Differentiable Tactile Simulator for Contact-rich Robotic Manipulation Zilin Si, Gu Zhang, Qingwei Ben, Branden Romero, Zhou Xian, Chao Liu, Chuang Gan

HyperHuman: Hyper-Realistic Human Generation with Latent Structural Diffusion Xian Liu, Jian Ren, Aliaksandr Siarohin, Ivan Skorokhodov, Yanyu Li, Dahua Lin, Xihui Liu, Ziwei Liu, Sergey Tulyakov

Analyzing and Improving Optimal-Transport-based Adversarial Networks Jaemoo Choi, Jaewoong Choi, Myungjoo Kang

GraphPulse: Topological representations for temporal graph property prediction Kiarash Shamsi, Farimah Poursafaei, Shenyang(Andy) Huang, Tran Gia Bao Ngo, Baris Coskunuzer, Cuneyt Akcora

Copilot4D: Learning Unsupervised World Models for Autonomous Driving via Discrete Diffusion Lunjun Zhang, Yuwen Xiong, Ze Yang, Sergio Casas, Rui Hu, Raquel Urtasun

Path Choice Matters for Clear Attributions in Path Methods Borui Zhang, Wenzhao Zheng, Jie Zhou, Jiwen Lu

Data-independent Module-aware Pruning for Hierarchical Vision Transformers Yang He, Joey Tianyi Zhou

Look, Remember and Reason: Grounded Reasoning in Videos with Language Models Apratim Bhattacharyya, Sunny Panchal, Reza Pourreza, Mingu Lee, Pulkit Madan, Roland Memisevic

MUSTARD: Mastering Uniform Synthesis of Theorem and Proof Data Yinya Huang, Xiaohan Lin, Zhengying Liu, Qingxing Cao, Huajian Xin, Haiming Wang, Zhenguo Li, Linqi Song, Xiaodan Liang

A Simple Romance Between Multi-Exit Vision Transformer and Token Reduction Dongyang Liu, Meina Kan, Shiguang Shan, Xilin CHEN

Stack Attention: Improving the Ability of Transformers to Model Hierarchical Patterns Brian DuSell, David Chiang

Guess & Sketch: Language Model Guided Transpilation Celine Lee, Abdulrahman Mahmoud, Michal Kurek, Simone Campanoni, David Brooks, Stephen Chong, Gu-Yeon Wei, Alexander Rush

Mean Field Theory in Deep Metric Learning Takuya Furusawa

The Alignment Problem from a Deep Learning Perspective Richard Ngo, Lawrence Chan, Sören Mindermann

Fast-ELECTRA for Efficient Pre-training Chengyu Dong, Liyuan Liu, Hao Cheng, Jingbo Shang, Jianfeng Gao, Xiaodong Liu

L2P-MIP: Learning to Presolve for Mixed Integer Programming Chang Liu, Zhichen Dong, Haobo Ma, Weilin Luo, Xijun Li, Bowen Pang, Jia Zeng, Junchi Yan

Piecewise Linear Parametrization of Policies: Towards Interpretable Deep Reinforcement Learning Maxime Wabartha, Joelle Pineau

Evoke: Evoking Critical Thinking Abilities in LLMs via Reviewer-Author Prompt Editing Xinyu Hu, Pengfei Tang, Simiao Zuo, Zihan Wang, Bowen Song, Qiang Lou, Jian Jiao, Denis Charles

OctoPack: Instruction Tuning Code Large Language Models Niklas Muennighoff, Qian Liu, Armel Zebaze, Qinkai Zheng, Binyuan Hui, Terry Yue Zhuo, Swayam Singh, Xiangru Tang, Leandro Von Werra, Shayne Longpre

Solving Inverse Problems with Latent Diffusion Models via Hard Data Consistency Bowen Song, Soo Min Kwon, Zecheng Zhang, Xinyu Hu, Qing Qu, Liyue Shen

Rethinking Backdoor Attacks on Dataset Distillation: A Kernel Method Perspective Ming-Yu Chung, Sheng-Yen Chou, Chia-Mu Yu, Pin-Yu Chen, Sy-Yen Kuo, Tsung-Yi Ho

Sparse Weight Averaging with Multiple Particles for Iterative Magnitude Pruning Moonseok Choi, Hyungi Lee, Giung Nam, Juho Lee

The Expressive Power of Transformers with Chain of Thought William Merrill, Ashish Sabharwal

Instructive Decoding: Instruction-Tuned Large Language Models are Self-Refiner from Noisy Instructions Taehyeon Kim, JOONKEE KIM, Gihun Lee, Se-Young Yun

What's In My Big Data? Yanai Elazar, Akshita Bhagia, Ian Magnusson, Abhilasha Ravichander, Dustin Schwenk, Alane Suhr, Pete Walsh, Dirk Groeneveld, Luca Soldaini, Sameer Singh, Hannaneh Hajishirzi, Noah Smith, Jesse Dodge

Social Reward: Evaluating and Enhancing Generative AI through Million-User Feedback from an Online Creative Community Arman Isajanyan, Artur Shatveryan, David Kocharian, Zhangyang Wang, Humphrey Shi

Language Model Detectors Are Easily Optimized Against Charlotte Nicks, Eric Mitchell, Rafael Rafailov, Archit Sharma, Christopher Manning, Chelsea Finn, Stefano Ermon

Sparse Autoencoders Find Highly Interpretable Features in Language Models Robert Huben, Hoagy Cunningham, Logan Smith, Aidan Ewart, Lee Sharkey

Brain decoding: toward real-time reconstruction of visual perception Yohann Benchetrit, Hubert Banville, Jean-Remi King

Generative Human Motion Stylization in Latent Space chuan guo, Yuxuan Mu, Xinxin Zuo, Peng Dai, Youliang Yan, Juwei Lu, Li Cheng

From Bricks to Bridges: Product of Invariances to Enhance Latent Space Communication Irene Cannistraci, Luca Moschella, Marco Fumero, Valentino Maiorca, Emanuele Rodolà

Poly-View Contrastive Learning Amitis Shidani, R Devon Hjelm, Jason Ramapuram, Russell Webb, Eeshan Gunesh Dhekane, Dan Busbridge

DAM: Towards a Foundation Model for Forecasting Luke Darlow, Qiwen Deng, Ahmed Hassan, Martin Asenov, Rajkarn Singh, Artjom Joosen, Adam Barker, Amos Storkey

SEABO: A Simple Search-Based Method for Offline Imitation Learning Jiafei Lyu, Xiaoteng Ma, Le Wan, Runze Liu, Xiu Li, Zongqing Lu

M3C: A Framework towards Convergent, Flexible, and Unsupervised Learning of Mixture Graph Matching and Clustering Jiaxin Lu, Zetian Jiang, Tianzhe Wang, Junchi Yan

Fine-Tuning Enhances Existing Mechanisms: A Case Study on Entity Tracking Nikhil Prakash, Tamar Shaham, Tal Haklay, Yonatan Belinkov, David Bau

SOInter: A Novel Deep Energy-Based Interpretation Method for Explaining Structured Output Models S. Fatemeh Seyyedsalehi, Mahdieh Baghshah, Hamid Rabiee

STARC: A General Framework For Quantifying Differences Between Reward Functions Joar Skalse, Lucy Farnik, Sumeet Motwani, Erik Jenner, Adam Gleave, Alessandro Abate

Automatic Functional Differentiation in JAX Min Lin

Denoising Diffusion Bridge Models Linqi Zhou, Aaron Lou, Samar Khanna, Stefano Ermon

GTA: A Geometry-Aware Attention Mechanism for Multi-View Transformers Takeru Miyato, Bernhard Jaeger, Max Welling, Andreas Geiger

Exploring Diffusion Time-steps for Unsupervised Representation Learning Zhongqi Yue, Jiankun Wang, Qianru Sun, Lei Ji, Eric Chang, Hanwang Zhang

LongLoRA: Efficient Fine-tuning of Long-Context Large Language Models Yukang Chen, Shengju Qian, Haotian Tang, Xin Lai, Zhijian Liu, Song Han, Jiaya Jia

Prediction Error-based Classification for Class-Incremental Learning Michał Zając, Tinne Tuytelaars, Gido van de Ven

SWAP: Sparse Entropic Wasserstein Regression for Robust Network Pruning Lei You, Hei Victor Cheng

An Unforgeable Publicly Verifiable Watermark for Large Language Models Aiwei Liu, Leyi Pan, Xuming Hu, Shuang Li, Lijie Wen, Irwin King, Philip Yu

BENO: Boundary-embedded Neural Operators for Elliptic PDEs Haixin Wang, Jiaxin Li, Anubhav Dwivedi, Kentaro Hara, Tailin Wu

Enhancing Human Experience in Human-Agent Collaboration: A Human-Centered Modeling Approach Based on Positive Human Gain Yiming Gao, Feiyu Liu, Liang Wang, Dehua Zheng, Zhenjie Lian, Weixuan Wang, Wenjin Yang, Siqin Li, Xianliang Wang, Wenhui Chen, Jing Dai, QIANG FU, Yang Wei, Lanxiao Huang, Wei Liu

Rethinking the Uniformity Metric in Self-Supervised Learning Xianghong Fang, Jian Li, Qiang Sun, Wang Benyou

BESA: Pruning Large Language Models with Blockwise Parameter-Efficient Sparsity Allocation Peng Xu, Wenqi Shao, Mengzhao Chen, Shitao Tang, Kaipeng Zhang, Gao Peng, Fengwei An, Yu Qiao, Ping Luo

OpenNeRF: Open Set 3D Neural Scene Segmentation with Pixel-Wise Features and Rendered Novel Views Francis Engelmann, Fabian Manhardt, Michael Niemeyer, Keisuke Tateno, Federico Tombari

ClimODE: Climate and Weather Forecasting with Physics-informed Neural ODEs Yogesh Verma, Markus Heinonen, Vikas Garg

FreeDyG: Frequency Enhanced Continuous-Time Dynamic Graph Model for Link Prediction Yuxing Tian, Yiyan Qi, Fan Guo

NetInfoF Framework: Measuring and Exploiting Network Usable Information Meng-Chieh Lee, Haiyang Yu, Jian Zhang, Vassilis N. Ioannidis, Xiang song, Soji Adeshina, Da Zheng, Christos Faloutsos

DrS: Learning Reusable Dense Rewards for Multi-Stage Tasks Tongzhou Mu, Minghua Liu, Hao Su

Reward-Consistent Dynamics Models are Strongly Generalizable for Offline Reinforcement Learning Fan-Ming Luo, Tian Xu, Xingchen Cao, Yang Yu

Annealing Self-Distillation Rectification Improves Adversarial Training Yu-Yu Wu, Hung-Jui Wang, Shang-Tse Chen

Self-Supervised Speech Quality Estimation and Enhancement Using Only Clean Speech Szu-Wei Fu, Kuo-Hsuan Hung, Yu Tsao, Yu-Chiang Frank Wang

LUM-ViT: Learnable Under-sampling Mask Vision Transformer for Bandwidth Limited Optical Signal Acquisition Lingfeng Liu, Dong Ni, Hangjie Yuan

Unsupervised Pretraining for Fact Verification by Language Model Distillation Adrian Bazaga, Pietro Lio, Gos Micklem

Intelligent Switching for Reset-Free RL Darshan Patil, Janarthanan Rajendran, Glen Berseth, Sarath Chandar

Learning with Mixture of Prototypes for Out-of-Distribution Detection Haodong Lu, Dong Gong, Shuo Wang, Jason Xue, Lina Yao, Kristen Moore

C-TPT: Calibrated Test-Time Prompt Tuning for Vision-Language Models via Text Feature Dispersion Hee Suk Yoon, Eunseop Yoon, Joshua Tian Jin Tee, Mark Hasegawa-Johnson, Yingzhen Li, Chang Yoo

Only Pay for What Is Uncertain: Variance-Adaptive Thompson Sampling Aadirupa Saha, Branislav Kveton

Masked Completion via Structured Diffusion with White-Box Transformers Druv Pai, Sam Buchanan, Ziyang Wu, Yaodong Yu, Yi Ma

Human Motion Diffusion as a Generative Prior Yonatan Shafir, Guy Tevet, Roy Kapon, Amit Bermano

LLMs Meet VLMs: Boost Open Vocabulary Object Detection with Fine-grained Descriptors Sheng JIn, Xueying Jiang, Jiaxing Huang, Lewei Lu, Shijian Lu

Teaching Large Language Models to Self-Debug Xinyun Chen, Maxwell Lin, Nathanael Schaerli, Denny Zhou

Hyper Evidential Deep Learning to Quantify Composite Classification Uncertainty Changbin Li, Kangshuo Li, Yuzhe Ou, Lance Kaplan, Audun Jøsang, Jin-Hee Cho, DONG HYUN JEONG, Feng Chen

Harnessing Joint Rain-/Detail-aware Representations to Eliminate Intricate Rains Wu Ran, Peirong Ma, Zhiquan He, Hao Ren, Hong Lu

Simplifying Transformer Blocks Bobby He, Thomas Hofmann

Structured Video-Language Modeling with Temporal Grouping and Spatial Grounding Yuanhao Xiong, Long Zhao, Boqing Gong, Ming-Hsuan Yang, Florian Schroff, Ting Liu, Cho-Jui Hsieh, Liangzhe Yuan

AlignDiff: Aligning Diverse Human Preferences via Behavior-Customisable Diffusion Model Zibin Dong, Yifu Yuan, Jianye HAO, Fei Ni, Yao Mu, YAN ZHENG, Yujing Hu, Tangjie Lv, Changjie Fan, Zhipeng Hu

Boosting Graph Anomaly Detection with Adaptive Message Passing Jingyan Chen, Guanghui Zhu, Chunfeng Yuan, Yihua Huang

GeoDiffusion: Text-Prompted Geometric Control for Object Detection Data Generation Kai Chen, Enze Xie, Zhe Chen, Yibo Wang, Lanqing HONG, Zhenguo Li, Dit-Yan Yeung

ReMasker: Imputing Tabular Data with Masked Autoencoding Tianyu Du, Luca Melis, Ting Wang

GAIA: a benchmark for General AI Assistants Grégoire Mialon, Clémentine Fourrier, Thomas Wolf, Yann LeCun, Thomas Scialom

Foundation Model-oriented Robustness: Robust Image Model Evaluation with Pretrained Models Peiyan Zhang, Haoyang Liu, Chaozhuo Li, Xing Xie, Sunghun Kim, Haohan Wang

ChatEval: Towards Better LLM-based Evaluators through Multi-Agent Debate Chi-Min Chan, Weize Chen, Yusheng Su, Jianxuan Yu, Wei Xue, Shanghang Zhang, Jie Fu, Zhiyuan Liu

Towards Aligned Layout Generation via Diffusion Model with Aesthetic Constraints Jian Chen, Ruiyi Zhang, Yufan Zhou, Changyou Chen

Self-RAG: Learning to Retrieve, Generate, and Critique through Self-Reflection Akari Asai, Zeqiu Wu, Yizhong Wang, Avi Sil, Hannaneh Hajishirzi

Real-time Photorealistic Dynamic Scene Representation and Rendering with 4D Gaussian Splatting Zeyu Yang, Hongye Yang, Zijie Pan, Li Zhang

Beyond Vanilla Variational Autoencoders: Detecting Posterior Collapse in Conditional and Hierarchical Variational Autoencoders Hien Dang, Tho-Huu Tran, Tan Nguyen, Nhat Ho

Weatherproofing Retrieval for Localization with Generative AI and Geometric Consistency Yannis Kalantidis, Mert Bulent SARIYILDIZ, Rafael Rezende, Philippe Weinzaepfel, Diane Larlus, Gabriela Csurka

Successor Heads: Recurring, Interpretable Attention Heads In The Wild Rhys Gould, Euan Ong, George Ogden, Arthur Conmy

Confidence-aware Reward Optimization for Fine-tuning Text-to-Image Models Kyuyoung Kim, Jongheon Jeong, Minyong An, Mohammad Ghavamzadeh, Krishnamurthy Dvijotham, Jinwoo Shin, Kimin Lee

Skill or Luck? Return Decomposition via Advantage Functions Hsiao-Ru Pan, David Ha

Dual RL: Unification and New Methods for Reinforcement and Imitation Learning Harshit Sikchi, Qinqing Zheng, Amy Zhang, Scott Niekum

Weaker MVI Condition: Extragradient Methods with Multi-Step Exploration Yifeng Fan, Yongqiang Li, Bo Chen

Learning to Act without Actions Dominik Schmidt, Minqi Jiang

Emergent Communication with Conversational Repair Mitja Nikolaus

Learning Nash Equilibria in Rank-1 Games Nikolas Patris, Ioannis Panageas

Generative Pre-training for Speech with Flow Matching Alexander Liu, Matthew Le, Apoorv Vyas, Bowen Shi, Andros Tjandra, Wei-Ning Hsu

FlashFFTConv: Efficient Convolutions for Long Sequences with Tensor Cores Dan Fu, Hermann Kumbong, Eric Nguyen, Christopher Re

Learning Large DAGs is Harder than you Think: Many Losses are Minimal for the Wrong DAG Jonas Seng, Matej Zečević, Devendra Singh Dhami, Kristian Kersting

Dissecting Sample Hardness: A Fine-Grained Analysis of Hardness Characterization Methods for Data-Centric AI Nabeel Seedat, Fergus Imrie, Mihaela van der Schaar

Chain-of-Knowledge: Grounding Large Language Models via Dynamic Knowledge Adapting over Heterogeneous Sources Xingxuan Li, Ruochen Zhao, Yew Ken Chia, Bosheng Ding, Shafiq Joty, Soujanya Poria, Lidong Bing

LanguageBind: Extending Video-Language Pretraining to N-modality by Language-based Semantic Alignment Bin Zhu, Bin Lin, Munan Ning, YANG YAN, Jiaxi Cui, WANG HongFa, Yatian Pang, Wenhao Jiang, Junwu Zhang, Zongwei Li, Cai Zhang, Zhifeng Li, Wei Liu, Yuan Li

SAN: Inducing Metrizability of GAN with Discriminative Normalized Linear Layer Yuhta Takida, Masaaki Imaizumi, Takashi Shibuya, Chieh-Hsin Lai, Toshimitsu Uesaka, Naoki Murata, Yuki Mitsufuji

Efficient Video Diffusion Models via Content-Frame Motion-Latent Decomposition Sihyun Yu, Weili Nie, De-An Huang, Boyi Li, Jinwoo Shin, anima anandkumar

Integrating Planning and Deep Reinforcement Learning via Automatic Induction of Task Substructures Jung-Chun Liu, Chi-Hsien Chang, Shao-Hua Sun, Tian-Li Yu

ToolLLM: Facilitating Large Language Models to Master 16000+ Real-world APIs Yujia Qin, Shihao Liang, Yining Ye, Kunlun Zhu, Lan Yan, Yaxi Lu, Yankai Lin, Xin Cong, Xiangru Tang, Bill Qian, Sihan Zhao, Lauren Hong, Runchu Tian, Ruobing Xie, Jie Zhou, Mark Gerstein, dahai li, Zhiyuan Liu, Maosong Sun

Scaling Laws for Associative Memories Vivien Cabannes, Elvis Dohmatob, Alberto Bietti

Neur2RO: Neural Two-Stage Robust Optimization Justin Dumouchelle, Esther Julien, Jannis Kurtz, Elias Khalil

Accelerating Distributed Stochastic Optimization via Self-Repellent Random Walks Jie Hu, Vishwaraj Doshi, Do Young Eun

Momentum Benefits Non-iid Federated Learning Simply and Provably Ziheng Cheng, Xinmeng Huang, Pengfei Wu, Kun Yuan

Deep Neural Networks Tend To Extrapolate Predictably Katie Kang, Amrith Setlur, Claire Tomlin, Sergey Levine

Conditional Instrumental Variable Regression with Representation Learning for Causal Inference Debo Cheng, Ziqi Xu, Jiuyong Li, Lin Liu, Jixue Liu, Thuc Le

Multi-Scale Representations by Varying Window Attention for Semantic Segmentation Haotian Yan, Ming Wu, Chuang Zhang

Towards Unified Multi-Modal Personalization: Large Vision-Language Models for Generative Recommendation and Beyond Tianxin Wei, Bowen Jin, Ruirui Li, Hansi Zeng, Zhengyang Wang, Jianhui Sun, Qingyu Yin, Hanqing Lu, Suhang Wang, Jingrui He, Xianfeng Tang

Enhancing High-Resolution 3D Generation through Pixel-wise Gradient Clipping Zijie Pan, Jiachen Lu, Xiatian Zhu, Li Zhang

Mechanistically analyzing the effects of fine-tuning on procedurally defined tasks Samyak Jain, Robert Kirk, Ekdeep Singh Lubana, Robert Dick, Hidenori Tanaka, Tim Rocktaeschel, Edward Grefenstette, David Krueger

Learning Personalized Causally Invariant Representations for Heterogeneous Federated Clients Xueyang Tang, Song Guo, Jie ZHANG, Jingcai Guo

Complex priors and flexible inference in recurrent circuits with dendritic nonlinearities Benjamin Lyo, Cristina Savin

Plug-and-Play Policy Planner for Large Language Model Powered Dialogue Agents Yang Deng, Wenxuan Zhang, Wai Lam, See-Kiong Ng, Tat-Seng Chua

Retroformer: Retrospective Large Language Agents with Policy Gradient Optimization Weiran Yao, Shelby Heinecke, Juan Carlos Niebles, Zhiwei Liu, Yihao Feng, Le Xue, Rithesh Ramapura Narasimha Murthy, Zeyuan Chen, Jianguo Zhang, Devansh Arpit, Ran Xu, Phil Mui, Huan Wang, Caiming Xiong, Silvio Savarese

Uncertainty Quantification via Stable Distribution Propagation Felix Petersen, Aashwin Mishra, Hilde Kuehne, Christian Borgelt, Oliver Deussen, Mikhail Yurochkin

Plug-and-Play Posterior Sampling under Mismatched Measurement and Prior Models Marien Renaud, Jiaming Liu, Valentin De Bortoli, Andres Almansa, Ulugbek Kamilov

Modeling Boundedly Rational Agents with Latent Inference Budgets Athul Jacob, Abhishek Gupta, Jacob Andreas

Learning model uncertainty as variance-minimizing instance weights Nishant Jain, Karthikeyan Shanmugam, Pradeep Shenoy

Score Regularized Policy Optimization through Diffusion Behavior Huayu Chen, Cheng Lu, Zhengyi Wang, Hang Su, Jun Zhu

Do Generated Data Always Help Contrastive Learning? Yifei Wang, Jizhe Zhang, Yisen Wang

Boosting the Adversarial Robustness of Graph Neural Networks: An OOD Perspective Kuan Li, YiWen Chen, Yang Liu, Jin Wang, QING HE, Minhao Cheng, Xiang Ao

Bandits Meet Mechanism Design to Combat Clickbait in Online Recommendation Thomas Kleine Buening, Aadirupa Saha, Christos Dimitrakakis, Haifeng Xu

RDesign: Hierarchical Data-efficient Representation Learning for Tertiary Structure-based RNA Design Cheng Tan, Yijie Zhang, Zhangyang Gao, Bozhen Hu, Siyuan Li, Zicheng Liu, Stan Z Li

Denoising Task Routing for Diffusion Models Byeongjun Park, Sangmin Woo, Hyojun Go, Jin-Young Kim, Changick Kim

Towards Enhancing Time Series Contrastive Learning: A Dynamic Bad Pair Mining Approach Xiang Lan, Hanshu Yan, Shenda Hong, Mengling Feng

Vanishing Gradients in Reinforcement Finetuning of Language Models Noam Razin, Hattie Zhou, Omid Saremi, Vimal Thilak, Arwen Bradley, Preetum Nakkiran, Joshua Susskind, Etai Littwin

Neuron Activation Coverage: Rethinking Out-of-distribution Detection and Generalization Yibing Liu, Chris Xing TIAN, Haoliang Li, Lei Ma, Shiqi Wang

Beyond Reverse KL: Generalizing Direct Preference Optimization with Diverse Divergence Constraints Chaoqi Wang, Yibo Jiang, Chenghao Yang, Han Liu, Yuxin Chen

Advancing Pose-Guided Image Synthesis with Progressive Conditional Diffusion Models Fei Shen, Hu Ye, Jun Zhang, Cong Wang, Xiao Han, Yang Wei

Linearity of Relation Decoding in Transformer Language Models Evan Hernandez, Arnab Sen Sharma, Tal Haklay, Kevin Meng, Martin Wattenberg, Jacob Andreas, Yonatan Belinkov, David Bau

Pathformer: Multi-scale Transformers with Adaptive Pathways for Time Series Forecasting Peng Chen, Yingying ZHANG, Yunyao Cheng, Yang Shu, Yihang Wang, Qingsong Wen, Bin Yang, Chenjuan Guo

STREAM: Spatio-TempoRal Evaluation and Analysis Metric for Video Generative Models Pum Jun Kim, Seojun Kim, Jaejun Yoo

TRAM: Bridging Trust Regions and Sharpness Aware Minimization Tom Sherborne, Naomi Saphra, Pradeep Dasigi, Hao Peng

Exploiting Causal Graph Priors with Posterior Sampling for Reinforcement Learning Mirco Mutti, Riccardo De Santi, Marcello Restelli, Alexander Marx, Giorgia Ramponi

Protein-ligand binding representation learning from fine-grained interactions Shikun Feng, Minghao Li, Yinjun JIA, Wei-Ying Ma, Yanyan Lan

Unleashing Large-Scale Video Generative Pre-training for Visual Robot Manipulation Hongtao Wu, Ya Jing, Chilam Cheang, Guangzeng Chen, Jiafeng Xu, Xinghang Li, Minghuan Liu, Hang Li, Tao Kong

Str2Str: A Score-based Framework for Zero-shot Protein Conformation Sampling Jiarui Lu, Bozitao Zhong, Zuobai Zhang, Jian Tang

Improved sampling via learned diffusions Lorenz Richter, Julius Berner

A Probabilistic Framework for Modular Continual Learning Lazar Valkov, Akash Srivastava, Swarat Chaudhuri, Charles Sutton

DP-SGD Without Clipping: The Lipschitz Neural Network Way Louis Béthune, Thomas Massena, Thibaut Boissin, Aurélien Bellet, Franck Mamalet, Yannick Prudent, Corentin Friedrich, Mathieu Serrurier, David Vigouroux

To the Cutoff... and Beyond? A Longitudinal Perspective on LLM Data Contamination Manley Roberts, Himanshu Thakur, Christine Herlihy, Colin White, Samuel Dooley

GAFormer: Enhancing Timeseries Transformers Through Group-Aware Embeddings Jingyun Xiao, Ran Liu, Eva Dyer

Robust Model Based Reinforcement Learning Using $\mathcal{L}_1$ Adaptive Control Minjun Sung, Sambhu Harimanas Karumanchi, Aditya Gahlawat, Naira HOVAKIMYAN

Federated Causal Discovery from Heterogeneous Data Loka Li, Ignavier Ng, Gongxu Luo, Biwei Huang, Guangyi Chen, Tongliang Liu, Bin Gu, Kun Zhang

Towards Few-Shot Adaptation of Foundation Models via Multitask Finetuning Zhuoyan Xu, Zhenmei Shi, Junyi Wei, Fangzhou Mu, Yin Li, Yingyu Liang

THOUGHT PROPAGATION: AN ANALOGICAL APPROACH TO COMPLEX REASONING WITH LARGE LANGUAGE MODELS Junchi Yu, Ran He, Rex Ying

Differentiable Learning of Generalized Structured Matrices for Efficient Deep Neural Networks Changwoo Lee, Hun-Seok Kim

Meta-VBO: Utilizing Prior Tasks in Optimizing Risk Measures with Gaussian Processes Quoc Phong Nguyen, Bryan Kian Hsiang Low, Patrick Jaillet

Expected flow networks in stochastic environments and two-player zero-sum games Marco Jiralerspong, Bilun Sun, Danilo Vucetic, Tianyu Zhang, Yoshua Bengio, Gauthier Gidel, Nikolay Malkin

Functional Bayesian Tucker Decomposition for Continuous-indexed Tensor Data Shikai Fang, Xin Yu, Zheng Wang, Shibo Li, Mike Kirby, Shandian Zhe

Plan-Seq-Learn: Language Model Guided RL for Solving Long Horizon Robotics Tasks Murtaza Dalal, Tarun Chiruvolu, Devendra Chaplot, Ruslan Salakhutdinov

iTransformer: Inverted Transformers Are Effective for Time Series Forecasting Yong Liu, Tengge Hu, Haoran Zhang, Haixu Wu, Shiyu Wang, Lintao Ma, Mingsheng Long

Implicit bias of SGD in $L_2$-regularized linear DNNs: One-way jumps from high to low rank Zihan Wang, Arthur Jacot

Understanding Reconstruction Attacks with the Neural Tangent Kernel and Dataset Distillation Noel Loo, Ramin Hasani, Mathias Lechner, Alexander Amini, Daniela Rus

Image Background Serves as Good Proxy for Out-of-distribution Data Sen Pei

NeuroBack: Improving CDCL SAT Solving using Graph Neural Networks Wenxi Wang, Yang Hu, Mohit Tiwari, Sarfraz Khurshid, Kenneth McMillan, Risto Miikkulainen

CARD: Channel Aligned Robust Blend Transformer for Time Series Forecasting xue wang, Tian Zhou, Qingsong Wen, Jinyang Gao, Bolin Ding, Rong Jin

Debiasing Attention Mechanism in Transformer without Demographics Shenyu Lu, Yipei Wang, Xiaoqian Wang

Functional Interpolation for Relative Positions improves Long Context Transformers Shanda Li, Chong You, Guru Guruganesh, Joshua Ainslie, Santiago Ontanon, Manzil Zaheer, Sumit Sanghai, Yiming Yang, Sanjiv Kumar, Srinadh Bhojanapalli

Cycle Consistency Driven Object Discovery Aniket Rajiv Didolkar, Anirudh Goyal, Yoshua Bengio

EmerDiff: Emerging Pixel-level Semantic Knowledge in Diffusion Models Koichi Namekata, Amirmojtaba Sabour, Sanja Fidler, Seung Wook Kim

Off-Policy Primal-Dual Safe Reinforcement Learning Zifan Wu, Bo Tang, Qian Lin, Chao Yu, Shangqin Mao, Qianlong Xie, Xingxing Wang, Dong Wang

AGILE3D: Attention Guided Interactive Multi-object 3D Segmentation Yuanwen Yue, Sabarinath Mahadevan, Jonas Schult, Francis Engelmann, Bastian Leibe, Konrad Schindler, Theodora Kontogianni

Improved Efficiency Based on Learned Saccade and Continuous Scene Reconstruction From Foveated Visual Sampling Jiayang Liu, Yiming Bu, Daniel Tso, Qinru Qiu

Graph Metanetworks for Processing Diverse Neural Architectures Derek Lim, Haggai Maron, Marc T Law, Jonathan Lorraine, James Lucas

Whittle Index with Multiple Actions and State Constraint for Inventory Management Chuheng Zhang, Xiangsen Wang, Wei Jiang, Xianliang Yang, Siwei Wang, Lei Song, Jiang Bian

A Statistical Analysis of Wasserstein Autoencoders for Intrinsically Low-dimensional Data Saptarshi Chakraborty, Peter Bartlett

Spurious Feature Diversification Improves Out-of-distribution Generalization Yong Lin, Lu Tan, Yifan HAO, Honam Wong, Hanze Dong, WEIZHONG ZHANG, Yujiu Yang, Tong Zhang

Relaxing the Additivity Constraints in Decentralized No-Regret High-Dimensional Bayesian Optimization Anthony Bardou, Patrick Thiran, Thomas Begin

On Stationary Point Convergence of PPO-Clip Ruinan Jin, Shuai Li, Baoxiang Wang

SineNet: Learning Temporal Dynamics in Time-Dependent Partial Differential Equations Xuan Zhang, Jacob Helwig, Yuchao Lin, Yaochen Xie, Cong Fu, Stephan Wojtowytsch, Shuiwang Ji

Conformal Language Modeling Victor Quach, Adam Fisch, Tal Schuster, Adam Yala, Jae Ho Sohn, Tommi Jaakkola, Regina Barzilay

SliceGPT: Compress Large Language Models by Deleting Rows and Columns Saleh Ashkboos, Maximilian Croci, Marcelo Gennari do Nascimento, Torsten Hoefler, James Hensman

DreamCraft3D: Hierarchical 3D Generation with Bootstrapped Diffusion Prior Jingxiang Sun, Bo Zhang, Ruizhi Shao, Lizhen Wang, Wen Liu, Zhenda Xie, Yebin Liu

NoiseDiffusion: Correcting Noise for Image Interpolation with Diffusion Models beyond Spherical Linear Interpolation Pengfei Zheng, Yonggang Zhang, Zhen Fang, Tongliang Liu, Defu Lian, Bo Han

Adversarial AutoMixup Huafeng Qin, Xin Jin, Yun Jiang, Mounîm El-Yacoubi, Xinbo Gao

Federated Recommendation with Additive Personalization Zhiwei Li, Guodong Long, Tianyi Zhou

Project and Probe: Sample-Efficient Adaptation by Interpolating Orthogonal Features Annie Chen, Yoonho Lee, Amrith Setlur, Sergey Levine, Chelsea Finn

Diffusion Model for Dense Matching Jisu Nam, Gyuseong Lee, Seonwoo Kim, Inès Hyeonsu Kim, Hyoungwon Cho, Seyeon Kim, Seungryong Kim

Model Merging by Uncertainty-Based Gradient Matching Nico Daheim, Thomas Möllenhoff, Edoardo M. Ponti, Iryna Gurevych, Mohammad Emtiyaz Khan

Dynamic Neural Response Tuning Tian Qiu, Xu Wenxiang, lin chen, Zhou Linyun, Zunlei Feng, Mingli Song

CoT3DRef: Chain-of-Thoughts Data-Efficient 3D Visual Grounding Eslam Abdelrahman, Mohamed Ayman Mohamed, Mahmoud Ahmed, Habib, Mohamed Elhoseiny

Interpretable Sparse System Identification: Beyond Recent Deep Learning Techniques on Time-Series Prediction Liu Xiaoyi, Duxin Chen, Wenjia Wei, Xia Zhu, Wenwu Yu

Chain of Thought Empowers Transformers to Solve Inherently Serial Problems Zhiyuan Li, Hong Liu, Denny Zhou, Tengyu Ma

Learning Optimal Contracts: How to Exploit Small Action Spaces Francesco Bacchiocchi, Matteo Castiglioni, Alberto Marchesi, Nicola Gatti

PTaRL: Prototype-based Tabular Representation Learning via Space Calibration Hangting Ye, Wei Fan, Xiaozhuang Song, Shun Zheng, He Zhao, Dandan Guo, Yi Chang

Global Optimality for Non-linear Constrained Restoration Problems via Invexity Samuel Pinilla, Jeyan Thiyagalingam

Large Language Models as Optimizers Chengrun Yang, Xuezhi Wang, Yifeng Lu, Hanxiao Liu, Quoc V Le, Denny Zhou, Xinyun Chen

Diffusion Posterior Sampling for Linear Inverse Problem Solving: A Filtering Perspective Zehao Dou, Yang Song

Score-based generative models break the curse of dimensionality in learning a family of sub-Gaussian distributions Frank Cole, Yulong Lu

LMUFormer: Low Complexity Yet Powerful Spiking Model With Legendre Memory Units Zeyu Liu, Gourav Datta, Anni Li, Peter Beerel

Alt-Text with Context: Improving Accessibility for Images on Twitter Nikita Srivatsan, Sofia Samaniego, Omar Florez, Taylor Berg-Kirkpatrick

On the Stability of Iterative Retraining of Generative Models on their own Data Quentin Bertrand, Joey Bose, Alexandre Duplessis, Marco Jiralerspong, Gauthier Gidel

Leveraging Optimization for Adaptive Attacks on Image Watermarks Nils Lukas, Abdelrahman Ahmed, Lucas Fenaux, Florian Kerschbaum

MERT: Acoustic Music Understanding Model with Large-Scale Self-supervised Training Yizhi Li, Ruibin Yuan, Ge Zhang, Yinghao MA, Xingran Chen, Hanzhi Yin, Chenghao Xiao, Chenghua Lin, Anton Ragni, Emmanouil Benetos, Norbert Gyenge, Roger Dannenberg, Ruibo Liu, Wenhu Chen, Gus Xia, Yemin Shi, Wenhao Huang, zili wang, Yike Guo, Jie Fu

A Multi-Level Framework for Accelerating Training Transformer Models Longwei Zou, Han Zhang, Yangdong Deng

DIAGNOSIS: Detecting Unauthorized Data Usages in Text-to-image Diffusion Models Zhenting Wang, Chen Chen, Lingjuan Lyu, Dimitris Metaxas, Shiqing Ma

Towards Robust Fidelity for Evaluating Explainability of Graph Neural Networks Xu Zheng, Farhad Shirani, Tianchun Wang, Wei Cheng, Zhuomin Chen, Haifeng Chen, Hua Wei, Dongsheng Luo

UniversalNER: Targeted Distillation from Large Language Models for Open Named Entity Recognition Wenxuan Zhou, Sheng Zhang, Yu Gu, Muhao Chen, Hoifung Poon

Closing the Curious Case of Neural Text Degeneration Matthew Finlayson, John Hewitt, Alexander Koller, Swabha Swayamdipta, Ashish Sabharwal

Meta Inverse Constrained Reinforcement Learning: Convergence Guarantee and Generalization Analysis Shicheng Liu, Minghui Zhu

Emu: Generative Pretraining in Multimodality Quan Sun, Qiying Yu, Yufeng Cui, Fan Zhang, Xiaosong Zhang, Yueze Wang, Hongcheng Gao, Jingjing Liu, Tiejun Huang, Xinlong Wang

Accelerated Sampling with Stacked Restricted Boltzmann Machines Jorge Fernandez-de-Cossio-Diaz, Clément Roussel, Simona Cocco, Remi Monasson

On the Expressivity of Objective-Specification Formalisms in Reinforcement Learning Rohan Subramani, Marcus Williams, Max Heitmann, Halfdan Holm, Charlie Griffin, Joar Skalse

Towards Training Without Depth Limits: Batch Normalization Without Gradient Explosion Alexandru Meterez, Amir Joudaki, Francesco Orabona, Alexander Immer, Gunnar Ratsch, Hadi Daneshmand

sRGB Real Noise Modeling via Noise-Aware Sampling with Normalizing Flows Dongjin Kim, Donggoo Jung, Sungyong Baik, Tae Hyun Kim

Bespoke Solvers for Generative Flow Models Neta Shaul, Juan Perez, Ricky T. Q. Chen, Ali Thabet, Albert Pumarola, Yaron Lipman

Q-Bench: A Benchmark for General-Purpose Foundation Models on Low-level Vision Haoning Wu, Zicheng Zhang, Erli Zhang, Chaofeng Chen, Liang Liao, Annan Wang, Chunyi Li, Wenxiu Sun, Qiong Yan, Guangtao Zhai, Weisi Lin

CausalLM is not optimal for in-context learning Nan Ding, Tomer Levinboim, Jialin Wu, Sebastian Goodman, Radu Soricut

Error Norm Truncation: Robust Training in the Presence of Data Noise for Text Generation Models Tianjian Li, Haoran Xu, Philipp Koehn, Daniel Khashabi, Kenton Murray

First-order ANIL provably learns representations despite overparametrisation Oğuz Kaan Yüksel, Etienne Boursier, Nicolas Flammarion

LEAP: Liberate Sparse-View 3D Modeling from Camera Poses Hanwen Jiang, Zhenyu Jiang, Yue Zhao, Qixing Huang

Behaviour Distillation Andrei Lupu, Chris Lu, Jarek Liesen, Robert Lange, Jakob Foerster

Fast Imitation via Behavior Foundation Models Matteo Pirotta, Andrea Tirinzoni, Ahmed Touati, Alessandro Lazaric, Yann Ollivier

Learning Semantic Proxies from Visual Prompts for Parameter-Efficient Fine-Tuning in Deep Metric Learning Li Ren, Chen Chen, Liqiang Wang, Kien Hua

Rethinking Channel Dimensions to Isolate Outliers for Low-bit Weight Quantization of Large Language Models Jung Hwan Heo, Jeonghoon Kim, Beomseok Kwon, Byeongwook Kim, Se Jung Kwon, Dongsoo Lee

Traveling Waves Encode The Recent Past and Enhance Sequence Learning T. Anderson Keller, Lyle Muller, Terrence Sejnowski, Max Welling

The Devil is in the Object Boundary: Towards Annotation-free Instance Segmentation using Foundation Models cheng shi, Sibei Yang

Unleashing the Potential of Fractional Calculus in Graph Neural Networks with FROND Qiyu Kang, Kai Zhao, Qinxu Ding, Feng Ji, Xuhao Li, Wenfei Liang, Yang Song, Wee Peng Tay

Neurosymbolic Grounding for Compositional World Models Atharva Sehgal, Arya Grayeli, Jennifer Sun, Swarat Chaudhuri

Are Models Biased on Text without Gender-related Language? Catarina Belém, Preethi Seshadri, Yasaman Razeghi, Sameer Singh

MG-TSD: Multi-Granularity Time Series Diffusion Models with Guided Learning Process Xinyao Fan, Yueying Wu, Chang XU, Yu-Hao Huang, Weiqing Liu, Jiang Bian

Robustifying and Boosting Training-Free Neural Architecture Search Zhenfeng He, Yao Shu, Zhongxiang Dai, Bryan Kian Hsiang Low

Learning Multi-Agent Communication from Graph Modeling Perspective Shengchao Hu, Li Shen, Ya Zhang, Dacheng Tao

MixSup: Mixed-grained Supervision for Label-efficient LiDAR-based 3D Object Detection Yuxue Yang, Lue Fan, Zhaoxiang Zhang

Federated Text-driven Prompt Generation for Vision-Language Models Chen Qiu, Xingyu Li, Chaithanya Kumar Mummadi, Madan Ganesh, Zhenzhen Li, Lu Peng, Wan-Yi Lin

Quick-Tune: Quickly Learning Which Pretrained Model to Finetune and How Sebastian Pineda Arango, Fabio Ferreira, Arlind Kadra, Frank Hutter, Josif Grabocka

LitCab: Lightweight Language Model Calibration over Short- and Long-form Responses Xin Liu, Muhammad Khalifa, Lu Wang

AuG-KD: Anchor-Based Mixup Generation for Out-of-Domain Knowledge Distillation Zihao Tang, Zheqi Lv, Shengyu Zhang, Yifan Zhou, Xinyu Duan, Fei Wu, Kun Kuang

Bilevel Optimization under Unbounded Smoothness: A New Algorithm and Convergence Analysis Jie Hao, Xiaochuan Gong, Mingrui Liu

FROSTER: Frozen CLIP is A Strong Teacher for Open-Vocabulary Action Recognition Xiaohu Huang, Hao Zhou, Kun Yao, Kai Han

Denoising Diffusion Step-aware Models Shuai Yang, Yukang Chen, Luozhou WANG, Shu Liu, YINGCONG CHEN

Learning to Jointly Understand Visual and Tactile Signals Yichen Li, Yilun Du, Chao Liu, Francis Williams, Michael Foshey, Benjamin Eckart, Jan Kautz, Joshua B Tenenbaum, Antonio Torralba, Wojciech Matusik

The optimality of kernel classifiers in Sobolev space Jianfa Lai, zhifan Li, Dongming Huang, Qian Lin

GIM: Learning Generalizable Image Matcher From Internet Videos Xuelun Shen, zhipeng cai, Wei Yin, Matthias Müller, Zijun Li, Kaixuan Wang, Xiaozhi Chen, Cheng Wang

Be Aware of the Neighborhood Effect: Modeling Selection Bias under Interference Haoxuan Li, Chunyuan Zheng, Sihao Ding, Peng Wu, Zhi Geng, Fuli Feng, Xiangnan He

An Emulator for Fine-tuning Large Language Models using Small Language Models Eric Mitchell, Rafael Rafailov, Archit Sharma, Chelsea Finn, Christopher Manning

The LLM Surgeon Tycho van der Ouderaa, Markus Nagel, Mart van Baalen, Tijmen Blankevoort

Selective Visual Representations Improve Convergence and Generalization for Embodied AI Ainaz Eftekhar, Kuo-Hao Zeng, Jiafei Duan, Ali Farhadi, Aniruddha Kembhavi, Ranjay Krishna

Discovering Temporally-Aware Reinforcement Learning Algorithms Matthew T Jackson, Chris Lu, Louis Kirsch, Robert Lange, Shimon Whiteson, Jakob Foerster

LipSim: A Provably Robust Perceptual Similarity Metric Sara Ghazanfari, Alexandre Araujo, Prashanth Krishnamurthy, Farshad Khorrami, Siddharth Garg

Multimodal Molecular Pretraining via Modality Blending Qiying Yu, Yudi Zhang, Yuyan Ni, Shikun Feng, Yanyan Lan, Hao Zhou, Jingjing Liu

Xformer: Hybrid X-Shaped Transformer for Image Denoising Jiale Zhang, Yulun Zhang, Jinjin Gu, Jiahua Dong, Linghe Kong, Xiaokang Yang

Reward Design for Justifiable Sequential Decision-Making Aleksa Sukovic, Goran Radanovic

Implicit Neural Representation Inference for Low-Dimensional Bayesian Deep Learning Panagiotis Dimitrakopoulos, Giorgos Sfikas, Christophoros Nikou

Whole-Song Hierarchical Generation of Symbolic Music Using Cascaded Diffusion Models Ziyu Wang, Lejun Min, Gus Xia

LoftQ: LoRA-Fine-Tuning-aware Quantization for Large Language Models Yixiao Li, Yifan Yu, Chen Liang, Nikos Karampatziakis, Pengcheng He, Weizhu Chen, Tuo Zhao

Empirical Likelihood for Fair Classification Pangpang Liu, Yichuan Zhao

Consistent algorithms for multi-label classification with macro-at-$k$ metrics Erik Schultheis, Wojciech Kotlowski, Marek Wydmuch, Rohit Babbar, Strom Borman, Krzysztof Dembczynski

Understanding Certified Training with Interval Bound Propagation Yuhao Mao, Mark N Müller, Marc Fischer, Martin Vechev

Point2SSM: Learning Morphological Variations of Anatomies from Point Clouds Jadie Adams, Shireen Elhabian

The Marginal Value of Momentum for Small Learning Rate SGD Runzhe Wang, Sadhika Malladi, Tianhao Wang, Kaifeng Lyu, Zhiyuan Li

Accelerating Sinkhorn algorithm with sparse Newton iterations Xun Tang, Michael Shavlovsky, Holakou Rahmanian, Elisa Tardini, Kiran Thekumparampil, Tesi Xiao, Lexing Ying

Domain constraints improve risk prediction when outcome data is missing Sidhika Balachandar, Nikhil Garg, Emma Pierson

Conformal Prediction via Regression-as-Classification Etash Guha, Shlok Natarajan, Thomas Möllenhoff, Mohammad Emtiyaz Khan, Eugene Ndiaye

What Makes a Good Prune? Maximal Unstructured Pruning for Maximal Cosine Similarity Gabryel Mason-Williams, Fredrik Dahlqvist

PB-LLM: Partially Binarized Large Language Models Zhihang Yuan, Yuzhang Shang, Zhen Dong

COLEP: Certifiably Robust Learning-Reasoning Conformal Prediction via Probabilistic Circuits Mintong Kang, Nezihe Merve Gürel, Linyi Li, Bo Li

Revisit and Outstrip Entity Alignment: A Perspective of Generative Models Lingbing Guo, Zhuo Chen, Jiaoyan Chen, Yin Fang, Wen Zhang, Huajun Chen

Catastrophic Jailbreak of Open-source LLMs via Exploiting Generation Yangsibo Huang, Samyak Gupta, Mengzhou Xia, Kai Li, Danqi Chen

Lipschitz Singularities in Diffusion Models Zhantao Yang, Ruili Feng, Han Zhang, Yujun Shen, Kai Zhu, Lianghua Huang, Yifei Zhang, Yu Liu, Deli Zhao, Jingren Zhou, Fan Cheng

VONet: Unsupervised Video Object Learning With Parallel U-Net Attention and Object-wise Sequential VAE Haonan Yu, Wei Xu

Closing the Gap between TD Learning and Supervised Learning - A Generalisation Point of View. Raj Ghugare, Matthieu Geist, Glen Berseth, Benjamin Eysenbach

Leftover Lunch: Advantage-based Offline Reinforcement Learning for Language Models Ashutosh Baheti, Ximing Lu, Faeze Brahman, Ronan Le Bras, Maarten Sap, Mark Riedl

Sparse MoE with Language Guided Routing for Multilingual Machine Translation Xinyu Zhao, Xuxi Chen, Yu Cheng, Tianlong Chen

Geometry-Aware Projective Mapping for Unbounded Neural Radiance Fields Junoh Lee, Hyunjun Jung, Jinhwi Park, Inhwan Bae, Hae-Gon Jeon

ADDP: Learning General Representations for Image Recognition and Generation with Alternating Denoising Diffusion Process Changyao Tian, Chenxin Tao, Jifeng Dai, Hao Li, Ziheng Li, Lewei Lu, Xiaogang Wang, Hongsheng Li, Gao Huang, Xizhou Zhu

Intriguing Properties of Generative Classifiers Priyank Jaini, Kevin Clark, Robert Geirhos

The Update-Equivalence Framework for Decision-Time Planning Samuel Sokota, Gabriele Farina, David Wu, Hengyuan Hu, Kevin A. Wang, Zico Kolter, Noam Brown

Zeroth-Order Optimization Meets Human Feedback: Provable Learning via Ranking Oracles Zhiwei Tang, Dmitry Rybin, Tsung-Hui Chang

Cross-Modal Contextualized Diffusion Models for Text-Guided Visual Generation and Editing Ling Yang, Zhilong Zhang, Zhaochen Yu, Jingwei Liu, Minkai Xu, Stefano Ermon, Bin CUI

ResFields: Residual Neural Fields for Spatiotemporal Signals Marko Mihajlovic, Sergey Prokudin, Marc Pollefeys, Siyu Tang

Reverse Diffusion Monte Carlo Xunpeng Huang, Hanze Dong, Yifan HAO, Yian Ma, Tong Zhang

Backdoor Secrets Unveiled: Identifying Backdoor Data with Optimized Scaled Prediction Consistency Soumyadeep Pal, Yuguang Yao, Ren Wang, Bingquan Shen, Sijia Liu

Hybrid Internal Model: Learning Agile Legged Locomotion with Simulated Robot Response Junfeng Long, ZiRui Wang, Quanyi Li, Liu Cao, Jiawei Gao, Jiangmiao Pang

Adversarial Imitation Learning via Boosting Jonathan Chang, Dhruv Sreenivas, Yingbing Huang, Kianté Brantley, Wen Sun

De novo Protein Design Using Geometric Vector Field Networks weian mao, Muzhi Zhu, Zheng Sun, Shuaike Shen, Lin Yuanbo Wu, Hao Chen, Chunhua Shen

DreamTime: An Improved Optimization Strategy for Diffusion-Guided 3D Generation Yukun Huang, Jianan Wang, Yukai Shi, Boshi Tang, Xianbiao Qi, Lei Zhang

Language Modeling Is Compression Gregoire Deletang, Anian Ruoss, Paul-Ambroise Duquenne, Elliot Catt, Tim Genewein, Christopher Mattern, Jordi Grau-Moya, Li Kevin Wenliang, Matthew Aitchison, Laurent Orseau, Marcus Hutter, Joel Veness

Pre-training LiDAR-based 3D Object Detectors through Colorization Tai-Yu Pan, Chenyang Ma, Tianle Chen, Cheng Perng Phoo, Katie Luo, Yurong You, Mark Campbell, Kilian Weinberger, Bharath Hariharan, Wei-Lun Chao

P$^2$OT: Progressive Partial Optimal Transport for Deep Imbalanced Clustering Chuyu Zhang, Hui Ren, Xuming He

Learning Multi-Faceted Prototypical User Interests Nhu-Thuat Tran, Hady W. Lauw

Merge, Then Compress: Demystify Efficient SMoE with Hints from Its Routing Policy Pingzhi Li, Zhenyu Zhang, Prateek Yadav, Yi-Lin Sung, Yu Cheng, Mohit Bansal, Tianlong Chen

Multi-modal Gaussian Process Variational Autoencoders for Neural and Behavioral Data Rabia Gondur, Usama Bin Sikandar, Evan Schaffer, Mikio Aoi, Stephen Keeley

Leveraging augmented-Lagrangian techniques for differentiating over infeasible quadratic programs in machine learning Antoine Bambade, Fabian Schramm, Adrien Taylor, Justin Carpentier

Towards Seamless Adaptation of Pre-trained Models for Visual Place Recognition Feng Lu, Lijun Zhang, Xiangyuan Lan, Shuting Dong, Yaowei Wang, Chun Yuan

Initializing Models with Larger Ones Zhiqiu Xu, Yanjie Chen, Kirill Vishniakov, Yida Yin, Zhiqiang Shen, trevor darrell, Lingjie Liu, Zhuang Liu

CLEX: Continuous Length Extrapolation for Large Language Models Guanzheng Chen, Xin Li, Zaiqiao Meng, Shangsong Liang, Lidong Bing

The Effective Horizon Explains Deep RL Performance in Stochastic Environments Cassidy Laidlaw, Banghua Zhu, Stuart Russell, Anca Dragan

Reasoning on Graphs: Faithful and Interpretable Large Language Model Reasoning Linhao Luo, Yuan-Fang Li, Reza Haffari, Shirui Pan

Alice Benchmarks: Connecting Real World Re-Identification with the Synthetic Xiaoxiao Sun, Yue Yao, Shengjin Wang, Hongdong Li, Liang Zheng

PINNACLE: PINN Adaptive ColLocation and Experimental points selection Gregory Kang Ruey Lau, Apivich Hemachandra, See-Kiong Ng, Bryan Kian Hsiang Low

Sudden Drops in the Loss: Syntax Acquisition, Phase Transitions, and Simplicity Bias in MLMs Angelica Chen, Ravid Shwartz-Ziv, Kyunghyun Cho, Matthew Leavitt, Naomi Saphra

Breaking Physical and Linguistic Borders: Multilingual Federated Prompt Tuning for Low-Resource Languages Wanru Zhao, Yihong Chen, Royson Lee, Xinchi Qiu, Yan Gao, Hongxiang Fan, Nic Lane

Generalized Schrödinger Bridge Matching Guan-Horng Liu, Yaron Lipman, Maximilian Nickel, Brian Karrer, Evangelos Theodorou, Ricky T. Q. Chen

Fair and Efficient Contribution Valuation for Vertical Federated Learning Zhenan Fan, Huang Fang, Xinglu Wang, Zirui Zhou, Jian Pei, Michael Friedlander, Yong Zhang

Neural Common Neighbor with Completion for Link Prediction Xiyuan Wang, Haotong Yang, Muhan Zhang

Effective Data Augmentation With Diffusion Models Brandon Trabucco, Kyle Doherty, Max Gurinas, Ruslan Salakhutdinov

Bridging Vision and Language Spaces with Assignment Prediction Jungin Park, Jiyoung Lee, Kwanghoon Sohn

Kernel Metric Learning for In-Sample Off-Policy Evaluation of Deterministic RL Policies Haanvid Lee, Tri Wahyu Guntara, Jongmin Lee, Yung-Kyun Noh, Kee-Eung Kim

Soft Robust MDPs and Risk-Sensitive MDPs: Equivalence, Policy Gradient, and Sample Complexity Runyu Zhang, Yang Hu, Na Li

MuSR: Testing the Limits of Chain-of-thought with Multistep Soft Reasoning Zayne Sprague, Xi Ye, Kaj Bostrom, Swarat Chaudhuri, Greg Durrett

Unveiling Options with Neural Network Decomposition Mahdi Alikhasi, Levi Lelis

Escape Sky-high Cost: Early-stopping Self-Consistency for Multi-step Reasoning Yiwei Li, Peiwen Yuan, Shaoxiong Feng, Boyuan Pan, Xinglin Wang, Bin Sun, Heda Wang, Kan Li

Faithful Rule Extraction for Differentiable Rule Learning Models Xiaxia Wang, David Jaime Tena Cucala, Bernardo Grau, Ian Horrocks

LOQA: Learning with Opponent Q-Learning Awareness Milad Aghajohari, Juan Duque, Timotheus Cooijmans, Aaron Courville

BatteryML: An Open-source Platform for Machine Learning on Battery Degradation Han Zhang, Xiaofan Gui, Shun Zheng, Ziheng Lu, Yuqi Li, Jiang Bian

Learning Conditional Invariances through Non-Commutativity Abhra Chaudhuri, Serban Georgescu, Anjan Dutta

IceFormer: Accelerated Inference with Long-Sequence Transformers on CPUs Yuzhen Mao, Martin Ester, Ke Li

Large-Vocabulary 3D Diffusion Model with Transformer Ziang Cao, Fangzhou Hong, Tong Wu, Liang Pan, Ziwei Liu

Fast Value Tracking for Deep Reinforcement Learning Frank Shih, Faming Liang

Negative Label Guided OOD Detection with Pretrained Vision-Language Models Xue JIANG, Feng Liu, Zhen Fang, Hong Chen, Tongliang Liu, Feng Zheng, Bo Han

MMICL: Empowering Vision-language Model with Multi-Modal In-Context Learning Haozhe Zhao, Zefan Cai, Shuzheng Si, Xiaojian Ma, Kaikai An, Liang Chen, Zixuan Liu, Sheng Wang, Wenjuan Han, Baobao Chang

LLM-Assisted Code Cleaning For Training Accurate Code Generators Naman Jain, Tianjun Zhang, Wei-Lin Chiang, Joseph E Gonzalez, Koushik Sen, Ion Stoica

Guiding Masked Representation Learning to Capture Spatio-Temporal Relationship of Electrocardiogram Yeongyeon Na, Minje Park, Yunwon Tae, Sunghoon Joo

Transformers can optimally learn regression mixture models Reese Pathak, Rajat Sen, Weihao Kong, Abhimanyu Das

The importance of feature preprocessing for differentially private linear optimization Ziteng Sun, Ananda Theertha Suresh, Aditya Krishna Menon

Improved Techniques for Training Consistency Models Yang Song, Prafulla Dhariwal

Lemur: Harmonizing Natural Language and Code for Language Agents Yiheng Xu, Hongjin SU, Chen Xing, Boyu Mi, Qian Liu, Weijia Shi, Binyuan Hui, FAN ZHOU, Yitao Liu, Tianbao Xie, Zhoujun Cheng, Siheng Zhao, Lingpeng Kong, Bailin Wang, Caiming Xiong, Tao Yu

Approximating Nash Equilibria in Normal-Form Games via Stochastic Optimization Ian Gemp, Luke Marris, Georgios Piliouras

Elucidating the Exposure Bias in Diffusion Models Mang Ning, Mingxiao Li, Jianlin Su, Albert Ali Salah, Itir Onal Ertugrul

Submodular Reinforcement Learning Manish Prajapat, Mojmir Mutny, Melanie Zeilinger, Andreas Krause

SuRe: Summarizing Retrievals using Answer Candidates for Open-domain QA of LLMs Jaehyung Kim, Jaehyun Nam, Sangwoo Mo, Jongjin Park, Sang-Woo Lee, Minjoon Seo, Jung-Woo Ha, Jinwoo Shin

BEND: Benchmarking DNA Language Models on Biologically Meaningful Tasks Frederikke Marin, Felix Teufel, Marc Horlacher, Dennis Madsen, Dennis Pultz, Ole Winther, Wouter Boomsma

Masked Distillation Advances Self-Supervised Transformer Architecture Search Caixia Yan, Xiaojun Chang, Zhihui Li, Lina Yao, Minnan Luo, Qinghua Zheng

AutoChunk: Automated Activation Chunk for Memory-Efficient Deep Learning Inference Xuanlei Zhao, Shenggan Cheng, Guangyang LU, Haotian Zhou, Bin Jia, Yang You

Habitat 3.0: A Co-Habitat for Humans, Avatars, and Robots Xavier Puig, Eric Undersander, Andrew Szot, Mikael Dallaire Cote, Tsung-Yen Yang, Ruslan Partsey, Ruta Desai, Alexander Clegg, Michal Hlavac, So Yeon Min, Vladimír Vondruš, Theophile Gervet, Vincent-Pierre Berges, John Turner, Oleksandr Maksymets, Zsolt Kira, Mrinal Kalakrishnan, Jitendra Malik, Devendra Chaplot, Unnat Jain, Dhruv Batra, Akshara Rai, Roozbeh Mottaghi

On the Markov Property of Neural Algorithmic Reasoning: Analyses and Methods Montgomery Bohde, Meng Liu, Alexandra Saxton, Shuiwang Ji

Light Schrödinger Bridge Aleksandr Korotin, Nikita Gushchin, Evgeny Burnaev

Exploring Effective Stimulus Encoding via Vision System Modeling for Visual Prostheses Chuanqing Wang, Di Wu, Chaoming Fang, Jie Yang, Mohamad Sawan

Long-Term Typhoon Trajectory Prediction: A Physics-Conditioned Approach Without Reanalysis Data Young-Jae Park, Minseok Seo, Doyi Kim, Hyeri Kim, Sanghoon Choi, Beomkyu Choi, Jeongwon Ryu, Sohee Son, Hae-Gon Jeon, Yeji Choi

QLLM: Accurate and Efficient Low-Bitwidth Quantization for Large Language Models Jing Liu, Ruihao Gong, Xiuying Wei, Zhiwei Dong, Jianfei Cai, Bohan Zhuang

REBAR: Retrieval-Based Reconstruction for Time-series Contrastive Learning Maxwell Xu, Alexander Moreno, Hui Wei, Benjamin M Marlin, James Rehg

Conserve-Update-Revise to Cure Generalization and Robustness Trade-off in Adversarial Training Shruthi Gowda, Bahram Zonooz, Elahe Arani

CompA: Addressing the Gap in Compositional Reasoning in Audio-Language Models Sreyan Ghosh, Ashish Seth, Sonal Kumar, Utkarsh Tyagi, Chandra Kiran Evuru, Ramaneswaran S, S Sakshi, Oriol Nieto, Ramani Duraiswami, Dinesh Manocha

Towards Robust Offline Reinforcement Learning under Diverse Data Corruption Rui Yang, Han Zhong, Jiawei Xu, Amy Zhang, Chongjie Zhang, Lei Han, Tong Zhang

Towards image compression with perfect realism at ultra-low bitrates Marlene Careil, Matthew J Muckley, Jakob Verbeek, Stéphane Lathuilière

Adapting to Distribution Shift by Visual Domain Prompt Generation Zhixiang Chi, Li Gu, Tao Zhong, Huan Liu, YUANHAO YU, Konstantinos Plataniotis, Yang Wang

WebArena: A Realistic Web Environment for Building Autonomous Agents Shuyan Zhou, Frank F Xu, Hao Zhu, Xuhui Zhou, Robert Lo, Abishek Sridhar, Xianyi Cheng, Tianyue Ou, Yonatan Bisk, Daniel Fried, Uri Alon, Graham Neubig

Modulated Phase Diffusor: Content-Oriented Feature Synthesis for Detecting Unknown Objects Aming Wu, Cheng Deng

Davidsonian Scene Graph: Improving Reliability in Fine-grained Evaluation for Text-to-Image Generation Jaemin Cho, Yushi Hu, Jason Baldridge, Roopal Garg, Peter Anderson, Ranjay Krishna, Mohit Bansal, Jordi Pont-Tuset, Su Wang

Demystifying Poisoning Backdoor Attacks from a Statistical Perspective Ganghua Wang, Xun Xian, Ashish Kundu, Jayanth Srinivasa, Xuan Bi, Mingyi Hong, Jie Ding

Zoology: Measuring and Improving Recall in Efficient Language Models Simran Arora, Sabri Eyuboglu, Aman Timalsina, Isys Johnson, Michael Poli, James Y Zou, Atri Rudra, Christopher Re

EfficientDM: Efficient Quantization-Aware Fine-Tuning of Low-Bit Diffusion Models YEFEI HE, Jing Liu, Weijia Wu, Hong Zhou, Bohan Zhuang

Subtractive Mixture Models via Squaring: Representation and Learning Lorenzo Loconte, Aleksanteri Sladek, Stefan Mengel, Martin Trapp, Arno Solin, Nicolas Gillis, Antonio Vergari

Robust agents learn causal world models Jonathan Richens, Tom Everitt

Selective Mixup Fine-Tuning for Optimizing Non-Decomposable Objectives Shrinivas Ramasubramanian, Harsh Rangwani, Sho Takemori, Kunal Samanta, Yuhei Umeda, Venkatesh Babu Radhakrishnan

Flat Minima in Linear Estimation and an Extended Gauss Markov Theorem Simon Segert

Quantifying and Enhancing Multi-modal Robustness with Modality Preference Zequn Yang, Yake Wei, Ce Liang, Di Hu

Addressing Signal Delay in Deep Reinforcement Learning Wei Wang, Dongqi Han, Xufang Luo, Dongsheng Li

What Algorithms can Transformers Learn? A Study in Length Generalization Hattie Zhou, Arwen Bradley, Etai Littwin, Noam Razin, Omid Saremi, Joshua Susskind, Samy Bengio, Preetum Nakkiran

iGraphMix: Input Graph Mixup Method for Node Classification Jongwon Jeong, Hoyeop Lee, Hyui Geon Yoon, Beomyoung Lee, Junhee Heo, Geonsoo Kim, Kim Jin Seon

Accurate Retraining-free Pruning for Pretrained Encoder-based Language Models Seungcheol Park, Hojun Choi, U Kang

Simple Hierarchical Planning with Diffusion Chang Chen, Fei Deng, Kenji Kawaguchi, Caglar Gulcehre, Sungjin Ahn

Task Adaptation from Skills: Information Geometry, Disentanglement, and New Objectives for Unsupervised Reinforcement Learning Yucheng Yang, Tianyi Zhou, Qiang HE, Lei Han, Mykola Pechenizkiy, Meng Fang

On the Provable Advantage of Unsupervised Pretraining Jiawei Ge, Shange Tang, Jianqing Fan, Chi Jin

Harnessing Density Ratios for Online Reinforcement Learning Philip Amortila, Dylan Foster, Nan Jiang, Ayush Sekhari, Tengyang Xie

Knowledge Card: Filling LLMs' Knowledge Gaps with Plug-in Specialized Language Models Shangbin Feng, Weijia Shi, Yuyang Bai, Vidhisha Balachandran, Tianxing He, Yulia Tsvetkov

Going Beyond Neural Network Feature Similarity: The Network Feature Complexity and Its Interpretation Using Category Theory Yiting Chen, Zhanpeng Zhou, Junchi Yan

CircuitNet 2.0: An Advanced Dataset for Promoting Machine Learning Innovations in Realistic Chip Design Environment Xun Jiang, zhuomin chai, Yuxiang Zhao, Yibo Lin, Runsheng Wang, Ru Huang

Tackling the Data Heterogeneity in Asynchronous Federated Learning with Cached Update Calibration Yujia Wang, Yuanpu Cao, Jingcheng Wu, Ruoyu Chen, Jinghui Chen

Linear attention is (maybe) all you need (to understand Transformer optimization) Kwangjun Ahn, Xiang Cheng, Minhak Song, Chulhee Yun, Ali Jadbabaie, Suvrit Sra

Decision ConvFormer: Local Filtering in MetaFormer is Sufficient for Decision Making Jeonghye Kim, Su Young Lee, Woojun Kim, Youngchul Sung

Controlling Vision-Language Models for Multi-Task Image Restoration Ziwei Luo, Fredrik K. Gustafsson, Zheng Zhao, Jens Sjölund, Thomas Schön

PRIME: Prioritizing Interpretability in Failure Mode Extraction Keivan Rezaei, Mehrdad Saberi, Mazda Moayeri, Soheil Feizi

Hebbian Learning based Orthogonal Projection for Continual Learning of Spiking Neural Networks Mingqing Xiao, Qingyan Meng, Zongpeng Zhang, Di He, Zhouchen Lin

Prompt Gradient Projection for Continual Learning Jingyang Qiao, Zhizhong Zhang, Xin Tan, Chengwei Chen, Yanyun Qu, Yong Peng, Yuan Xie

Scaling for Training Time and Post-hoc Out-of-distribution Detection Enhancement Kai Xu, Rongyu Chen, Gianni Franchi, Angela Yao

TAIL: Task-specific Adapters for Imitation Learning with Large Pretrained Models Zuxin Liu, Jesse Zhang, Kavosh Asadi, Yao Liu, DING ZHAO, Shoham Sabach, Rasool Fakoor

Proving Test Set Contamination in Black-Box Language Models Yonatan Oren, Nicole Meister, Niladri Chatterji, Faisal Ladhak, Tatsunori Hashimoto

MAPE-PPI: Towards Effective and Efficient Protein-Protein Interaction Prediction via Microenvironment-Aware Protein Embedding Lirong Wu, Yijun Tian, Yufei Huang, Siyuan Li, Haitao Lin, Nitesh Chawla, Stan Z Li

How Well Do Supervised 3D Models Transfer to Medical Imaging Tasks? Wenxuan Li, Alan Yuille, Zongwei Zhou

Large Brain Model for Learning Generic Representations with Tremendous EEG Data in BCI Wei-Bang Jiang, Liming Zhao, Bao-liang Lu

Achieving Fairness in Multi-Agent MDP Using Reinforcement Learning Peizhong Ju, Arnob Ghosh, Ness Shroff

A ROBUST DIFFERENTIAL NEURAL ODE OPTIMIZER Panagiotis Theodoropoulos, Guan-Horng Liu, Tianrong Chen, Augustinos Saravanos, Evangelos Theodorou

VQGraph: Rethinking Graph Representation Space for Bridging GNNs and MLPs Ling Yang, Ye Tian, Minkai Xu, Zhongyi Liu, Shenda Hong, Wei Qu, Wentao Zhang, Bin CUI, Muhan Zhang, Jure Leskovec

MOFDiff: Coarse-grained Diffusion for Metal-Organic Framework Design Xiang Fu, Tian Xie, Andrew Rosen, Tommi Jaakkola, Jake Smith

CoVLM: Composing Visual Entities and Relationships in Large Language Models Via Communicative Decoding Junyan Li, Delin Chen, Yining Hong, Zhenfang Chen, Peihao Chen, Yikang Shen, Chuang Gan

Sample-Efficient Linear Representation Learning from Non-IID Non-Isotropic Data Thomas T. Zhang, Leonardo Felipe Toso, James Anderson, Nikolai Matni

Hybrid Directional Graph Neural Network for Molecules Junyi An, Chao Qu, Zhipeng Zhou, Fenglei Cao, Xu Yinghui, Yuan Qi, Furao Shen

Sparsistency for inverse optimal transport Francisco Andrade, Gabriel Peyré, Clarice Poon

SALMONN: Towards Generic Hearing Abilities for Large Language Models Changli Tang, Wenyi Yu, Guangzhi Sun, Xianzhao Chen, Tian Tan, Wei Li, Lu Lu, Zejun MA, Chao Zhang

Privately Aligning Language Models with Reinforcement Learning Fan Wu, Huseyin Inan, Arturs Backurs, Varun Chandrasekaran, Janardhan Kulkarni, Robert Sim

TiC-CLIP: Continual Training of CLIP Models Saurabh Garg, Mehrdad Farajtabar, Hadi Pouransari, Raviteja Vemulapalli, Sachin Mehta, Oncel Tuzel, Vaishaal Shankar, Fartash Faghri

MINDE: Mutual Information Neural Diffusion Estimation Giulio Franzese, Mustapha BOUNOUA, Pietro Michiardi

SOHES: Self-supervised Open-world Hierarchical Entity Segmentation Shengcao Cao, Jiuxiang Gu, Jason Kuen, Hao Tan, Ruiyi Zhang, Handong Zhao, Ani Nenkova, Liangyan Gui, Tong Sun, Yu-Xiong Wang

EmerNeRF: Emergent Spatial-Temporal Scene Decomposition via Self-Supervision Jiawei Yang, Boris Ivanovic, Or Litany, Xinshuo Weng, Seung Wook Kim, Boyi Li, Tong Che, Danfei Xu, Sanja Fidler, Marco Pavone, Yue Wang

Convergence of Bayesian Bilevel Optimization Shi Fu, Fengxiang He, Xinmei Tian, Dacheng Tao

Training Graph Transformers via Curriculum-Enhanced Attention Distillation Yisong Huang, Jin Li, Xinlong Chen, Yang-Geng Fu

Alleviating Exposure Bias in Diffusion Models through Sampling with Shifted Time Steps Mingxiao Li, Tingyu Qu, Ruicong Yao, Wei Sun, Marie-Francine Moens

GraphCare: Enhancing Healthcare Predictions with Personalized Knowledge Graphs Pengcheng Jiang, Cao (Danica) Xiao, Adam Cross, Jimeng Sun

Consistent Video-to-Video Transfer Using Synthetic Dataset Jiaxin Cheng, Tianjun Xiao, Tong He

Peering Through Preferences: Unraveling Feedback Acquisition for Aligning Large Language Models Hritik Bansal, John Dang, Aditya Grover

InterpGNN: Understand and Improve Generalization Ability of Transdutive GNNs through the Lens of Interplay between Train and Test Nodes Jiawei Sun, Kailai Li, Ruoxin Chen, Jie LI, Chentao Wu, Yue Ding, Junchi Yan

Vision-by-Language for Training-Free Compositional Image Retrieval Shyamgopal Karthik, Karsten Roth, Massimiliano Mancini, Zeynep Akata

Democratizing Fine-grained Visual Recognition with Large Language Models Mingxuan Liu, Subhankar Roy, Wenjing Li, Zhun Zhong, Nicu Sebe, Elisa Ricci

Sample-Efficient Learning of POMDPs with Multiple Observations In Hindsight Jiacheng Guo, Minshuo Chen, Huan Wang, Caiming Xiong, Mengdi Wang, Yu Bai

LDReg: Local Dimensionality Regularized Self-Supervised Learning Hanxun Huang, Ricardo Campello, Sarah Erfani, Xingjun Ma, Michael E. Houle, James Bailey

Large Language Models as Analogical Reasoners Michihiro Yasunaga, Xinyun Chen, Yujia Li, Panupong Pasupat, Jure Leskovec, Percy Liang, Ed H. Chi, Denny Zhou

BayesDiff: Estimating Pixel-wise Uncertainty in Diffusion via Bayesian Inference Siqi Kou, Lei Gan, Dequan Wang, Chongxuan Li, Zhijie Deng

Sliced Denoising: A Physics-Informed Molecular Pre-Training Method Yuyan Ni, Shikun Feng, Wei-Ying Ma, Zhi-Ming Ma, Yanyan Lan

COPlanner: Plan to Roll Out Conservatively but to Explore Optimistically for Model-Based RL Xiyao Wang, Ruijie Zheng, Yanchao Sun, Ruonan Jia, Wichayaporn Wongkamjan, Huazhe Xu, Furong Huang

Graph-based Virtual Sensing from Sparse and Partial Multivariate Observations Giovanni De Felice, Andrea Cini, Daniele Zambon, Vladimir Gusev, Cesare Alippi

BioBridge: Bridging Biomedical Foundation Models via Knowledge Graphs Zifeng Wang, Zichen Wang, Balasubramaniam Srinivasan, Vassilis N. Ioannidis, Huzefa Rangwala, RISHITA ANUBHAI

Inducing High Energy-Latency of Large Vision-Language Models with Verbose Images Kuofeng Gao, Yang Bai, Jindong Gu, Shu-Tao Xia, Philip Torr, Zhifeng Li, Wei Liu

From Molecules to Materials: Pre-training Large Generalizable Models for Atomic Property Prediction Nima Shoghi, Adeesh Kolluru, John Kitchin, Zachary Ulissi, Larry Zitnick, Brandon Wood

Efficient Backdoor Attacks for Deep Neural Networks in Real-world Scenarios Ziqiang Li, Hong Sun, Pengfei Xia, Heng Li, Beihao Xia, Yi Wu, Bin Li

Constraint-Free Structure Learning with Smooth Acyclic Orientations Riccardo Massidda, Francesco Landolfi, Martina Cinquini, Davide Bacciu

Function Vectors in Large Language Models Eric Todd, Millicent Li, Arnab Sen Sharma, Aaron Mueller, Byron Wallace, David Bau

Scaling Supervised Local Learning with Augmented Auxiliary Networks Chenxiang Ma, Jibin Wu, Chenyang Si, KC Tan

Towards 3D Molecule-Text Interpretation in Language Models Sihang Li, Zhiyuan Liu, Yanchen Luo, Xiang Wang, Xiangnan He, Kenji Kawaguchi, Tat-Seng Chua, Qi Tian

Beyond Stationarity: Convergence Analysis of Stochastic Softmax Policy Gradient Methods Sara Klein, Simon Weissmann, Leif Döring

Near-Optimal Solutions of Constrained Learning Problems Juan Elenter, Luiz Chamon, Alejandro Ribeiro

Motion Guidance: Diffusion-Based Image Editing with Differentiable Motion Estimators Daniel Geng, Andrew Owens

Quasi-Monte Carlo for 3D Sliced Wasserstein Khai Nguyen, Nicola Bariletto, Nhat Ho

Chain of Log-Concave Markov Chains Saeed Saremi, Ji Won Park, Francis Bach

Adversarial Feature Map Pruning for Backdoor Dong HUANG, Qingwen Bu

A Simple and Scalable Representation for Graph Generation Yunhui Jang, Seul Lee, Sungsoo Ahn

NEFTune: Noisy Embeddings Improve Instruction Finetuning Neel Jain, Ping-yeh Chiang, Yuxin Wen, John Kirchenbauer, Hong-Min Chu, Gowthami Somepalli, Brian Bartoldson, Bhavya Kailkhura, Avi Schwarzschild, Aniruddha Saha, Micah Goldblum, Jonas Geiping, Tom Goldstein

Localizing and Editing Knowledge In Text-to-Image Generative Models Samyadeep Basu, Nanxuan Zhao, Vlad Morariu, Soheil Feizi, Varun Manjunatha

GlucoBench: Curated List of Continuous Glucose Monitoring Datasets with Prediction Benchmarks Renat Sergazinov, Elizabeth Chun, Valeriya Rogovchenko, Nathaniel Fernandes, Nicholas Kasman, Irina Gaynanova

The Truth is in There: Improving Reasoning in Language Models with Layer-Selective Rank Reduction Pratyusha Sharma, Jordan Ash, Dipendra Kumar Misra

Facing the Elephant in the Room: Visual Prompt Tuning or Full finetuning? Cheng Han, Qifan Wang, Yiming Cui, Wenguan Wang, Lifu Huang, Siyuan Qi, Dongfang Liu

Leveraging Low-Rank and Sparse Recurrent Connectivity for Robust Closed-Loop Control Neehal Tumma, Mathias Lechner, Noel Loo, Ramin Hasani, Daniela Rus

GRAPH-CONSTRAINED DIFFUSION FOR END-TO-END PATH PLANNING DINGYUAN SHI, Yongxin Tong, Zimu Zhou, Ke Xu, Zheng Wang, Jieping Ye

LRR: Language-Driven Resamplable Continuous Representation against Adversarial Tracking Attacks Jianlang Chen, Xuhong Ren, Qing Guo, Felix Juefei-Xu, Di Lin, Wei Feng, Lei Ma, Jianjun Zhao

ARGS: Alignment as Reward-Guided Search Maxim Khanov, Jirayu Burapacheep, Yixuan Li

H-GAP: Humanoid Control with a Generalist Planner Zhengyao Jiang, Yingchen Xu, Nolan Wagener, Yicheng Luo, Michael Janner, Edward Grefenstette, Tim Rocktaeschel, Yuandong Tian

Uncertainty-aware Constraint Inference in Inverse Constrained Reinforcement Learning Sheng Xu, Guiliang Liu

Neural Auto-designer for Enhanced Quantum Kernels Cong Lei, Yuxuan Du, Peng Mi, Jun Yu, Tongliang Liu

The False Promise of Imitating Proprietary Language Models Arnav Gudibande, Eric Wallace, Charlie Snell, Xinyang Geng, Hao Liu, Pieter Abbeel, Sergey Levine, Dawn Song

InstaFlow: One Step is Enough for High-Quality Diffusion-Based Text-to-Image Generation Xingchao Liu, Xiwen Zhang, Jianzhu Ma, Jian Peng, Qiang Liu

Learning Delays in Spiking Neural Networks using Dilated Convolutions with Learnable Spacings Ilyass Hammouamri, Ismail Khalfaoui Hassani, Timothée Masquelier

Matcher: Segment Anything with One Shot Using All-Purpose Feature Matching Yang Liu, Muzhi Zhu, Hengtao Li, Hao Chen, Xinlong Wang, Chunhua Shen

Distinguished In Uniform: Self-Attention Vs. Virtual Nodes Eran Rosenbluth, Jan Tönshoff, Martin Ritzert, Berke Kisin, Martin Grohe

Minimax optimality of convolutional neural networks for infinite dimensional input-output problems and separation from kernel methods Yuto Nishimura, Taiji Suzuki

Improving LoRA in Privacy-preserving Federated Learning Youbang Sun, Zitao Li, Yaliang Li, Bolin Ding

Sparse Spiking Neural Network: Exploiting Heterogeneity in Timescales for Pruning Recurrent SNN Biswadeep Chakraborty, Beomseok Kang, Harshit Kumar, Saibal Mukhopadhyay

Predicting Emergent Abilities with Infinite Resolution Evaluation Shengding Hu, Xin Liu, Xu Han, Xinrong Zhang, Chaoqun He, Weilin Zhao, Yankai Lin, Ning Ding, Zebin Ou, Guoyang Zeng, Zhiyuan Liu, Maosong Sun

End-to-End (Instance)-Image Goal Navigation through Correspondence as an Emergent Phenomenon Guillaume Bono, Leonid Antsfeld, Boris Chidlovskii, Philippe Weinzaepfel, Christian Wolf

Deep Orthogonal Hypersphere Compression for Anomaly Detection Yunhe Zhang, Yan Sun, Jinyu Cai, Jicong Fan

DyVal: Dynamic Evaluation of Large Language Models for Reasoning Tasks Kaijie Zhu, Jiaao Chen, Jindong Wang, Neil Gong, Diyi Yang, Xing Xie

Tool-Augmented Reward Modeling Lei Li, Yekun Chai, Shuohuan Wang, Yu Sun, Hao Tian, Ningyu Zhang, hua wu

Sign2GPT: Leveraging Large Language Models for Gloss-Free Sign Language Translation Ryan Wong, Necati Cihan Camgoz, Richard Bowden

Adaptive deep spiking neural network with global-local learning via balanced excitatory and inhibitory mechanism Tingting Jiang, Qi Xu, Xuming Ran, Jiangrong Shen, Pan Lv, Qiang Zhang, Gang Pan

PF-LRM: Pose-Free Large Reconstruction Model for Joint Pose and Shape Prediction Peng Wang, Hao Tan, Sai Bi, Yinghao Xu, Fujun Luan, Kalyan Sunkavalli, Wenping Wang, Zexiang Xu, Kai Zhang

TabR: Tabular Deep Learning Meets Nearest Neighbors Yury Gorishniy, Ivan Rubachev, Nikolay Kartashev, Daniil Shlenskii, Akim Kotelnikov, Artem Babenko

Personalize Segment Anything Model with One Shot Renrui Zhang, Zhengkai Jiang, Ziyu Guo, Shilin Yan, Junting Pan, Hao Dong, Yu Qiao, Gao Peng, Hongsheng Li

Less is More: Fewer Interpretable Region via Submodular Subset Selection Ruoyu Chen, Hua Zhang, Siyuan Liang, Jingzhi Li, Xiaochun Cao

Knowledge Fusion of Large Language Models Fanqi Wan, Xinting Huang, Deng Cai, Xiaojun Quan, Wei BI, Shuming Shi

Polynormer: Polynomial-Expressive Graph Transformer in Linear Time Chenhui Deng, Zichao Yue, Zhiru Zhang

Circuit Component Reuse Across Tasks in Transformer Language Models Jack Merullo, Carsten Eickhoff, Ellie Pavlick

MiniGPT-4: Enhancing Vision-Language Understanding with Advanced Large Language Models Deyao Zhu, jun chen, Xiaoqian Shen, Xiang Li, Mohamed Elhoseiny

Interpreting CLIP's Image Representation via Text-Based Decomposition Yossi Gandelsman, Alexei Efros, Jacob Steinhardt

Intriguing Properties of Data Attribution on Diffusion Models Xiaosen Zheng, Tianyu Pang, Chao Du, Jing Jiang, Min Lin

Protein-Ligand Interaction Prior for Binding-aware 3D Molecule Diffusion Models Zhilin Huang, Ling Yang, Xiangxin Zhou, Zhilong Zhang, Wentao Zhang, Xiawu Zheng, Jie Chen, Yu Wang, Bin CUI, Wenming Yang

Tree Search-Based Policy Optimization under Stochastic Execution Delay David Valensi, Esther Derman, Shie Mannor, Gal Dalal

MAMBA: an Effective World Model Approach for Meta-Reinforcement Learning Zohar Rimon, Tom Jurgenson, Orr Krupnik, Gilad Adler, Aviv Tamar

Listen, Think, and Understand Yuan Gong, Hongyin Luo, Alexander Liu, Leonid Karlinsky, James R Glass

TEMPO: Prompt-based Generative Pre-trained Transformer for Time Series Forecasting Defu Cao, Furong Jia, Sercan Arik, Tomas Pfister, Yixiang Zheng, Wen Ye, Yan Liu

METRA: Scalable Unsupervised RL with Metric-Aware Abstraction Seohong Park, Oleh Rybkin, Sergey Levine

Transformer-Modulated Diffusion Models for Probabilistic Multivariate Time Series Forecasting Yuxin Li, Wenchao Chen, XINYUE HU, Bo Chen, baolin sun, Mingyuan Zhou

The Reversal Curse: LLMs trained on “A is B” fail to learn “B is A” Lukas Berglund, Meg Tong, Maximilian Kaufmann, Mikita Balesni, Asa Stickland, Tomek Korbak, Owain Evans

Energy-guided Entropic Neural Optimal Transport Petr Mokrov, Aleksandr Korotin, Alexander Kolesov, Nikita Gushchin, Evgeny Burnaev

VDC: Versatile Data Cleanser based on Visual-Linguistic Inconsistency by Multimodal Large Language Models Zihao Zhu, Mingda Zhang, Shaokui Wei, Bingzhe Wu, Baoyuan Wu

Causal Inference with Conditional Front-Door Adjustment and Identifiable Variational Autoencoder Ziqi Xu, Debo Cheng, Jiuyong Li, Jixue Liu, Lin Liu, Kui Yu

Tensor Trust: Interpretable Prompt Injection Attacks from an Online Game Sam Toyer, Olivia Watkins, Ethan Mendes, Justin Svegliato, Luke Bailey, Tiffany Wang, Isaac Ong, Karim Elmaaroufi, Pieter Abbeel, trevor darrell, Alan Ritter, Stuart Russell

Faster Sampling from Log-Concave Densities over Polytopes via Efficient Linear Solvers Oren Mangoubi, Nisheeth Vishnoi

Contrastive Preference Learning: Learning from Human Feedback without Reinforcement Learning Joey Hejna, Rafael Rafailov, Harshit Sikchi, Chelsea Finn, Scott Niekum, W. Bradley Knox, Dorsa Sadigh

Koopman-based generalization bound: New aspect for full-rank weights Yuka Hashimoto, Sho Sonoda, Isao Ishikawa, Atsushi Nitanda, Taiji Suzuki

Statistically Optimal $K$-means Clustering via Nonnegative Low-rank Semidefinite Programming Yubo Zhuang, Xiaohui Chen, Yun Yang, Richard Zhang

Mixture-of-Experts Meets Instruction Tuning: A Winning Combination for Large Language Models Sheng Shen, Le Hou, Yanqi Zhou, Nan Du, Shayne Longpre, Jason Wei, Hyung Won Chung, Barret Zoph, William Fedus, Xinyun Chen, Tu Vu, Yuexin Wu, Wuyang Chen, Albert Webson, Yunxuan Li, Vincent Zhao, Hongkun Yu, Kurt Keutzer, trevor darrell, Denny Zhou

Relay Diffusion: Unifying diffusion process across resolutions for image synthesis Jiayan Teng, Wendi Zheng, Ming Ding, Wenyi Hong, Jianqiao Wangni, Zhuoyi Yang, Jie Tang

Conditional Variational Diffusion Models Gabriel della Maggiora, Luis A. Croquevielle, Nikita Deshpande, Harry Horsley, Thomas Heinis, Artur Yakimovich

PoSE: Efficient Context Window Extension of LLMs via Positional Skip-wise Training Dawei Zhu, Nan Yang, Liang Wang, Yifan Song, Wenhao Wu, Furu Wei, Sujian Li

A Benchmark for Learning to Translate a New Language from One Grammar Book Garrett Tanzer, Mirac Suzgun, Eline Visser, Dan Jurafsky, Luke Melas-Kyriazi

Open the Black Box: Step-based Policy Updates for Temporally-Correlated Episodic Reinforcement Learning Ge Li, Hongyi Zhou, Dominik Roth, Serge Thilges, Fabian Otto, Rudolf Lioutikov, Gerhard Neumann

Contrastive Learning is Spectral Clustering on Similarity Graph Zhiquan Tan, Yifan Zhang, Jingqin Yang, Yang Yuan

Synapse: Trajectory-as-Exemplar Prompting with Memory for Computer Control Longtao Zheng, Rundong Wang, Xinrun Wang, Bo An

A Symmetry-Aware Exploration of Bayesian Neural Network Posteriors Olivier Laurent, Emanuel Aldea, Gianni Franchi

Self-Supervised Contrastive Learning for Long-term Forecasting Junwoo Park, Daehoon Gwak, Jaegul Choo, Edward Choi

RA-DIT: Retrieval-Augmented Dual Instruction Tuning Victoria Lin, Xilun Chen, Mingda Chen, Weijia Shi, Maria Lomeli, Richard James, Pedro Rodriguez, Jacob Kahn, Gergely Szilvasy, Mike Lewis, Luke Zettlemoyer, Scott Yih

Text-to-3D with Classifier Score Distillation Xin Yu, Yuan-Chen Guo, Yangguang Li, Ding Liang, Song-Hai Zhang, XIAOJUAN QI

One-shot Empirical Privacy Estimation for Federated Learning Galen Andrew, Peter Kairouz, Sewoong Oh, Alina Oprea, H. Brendan McMahan, Vinith Suriyakumar

Rethinking Model Ensemble in Transfer-based Adversarial Attacks Huanran Chen, Yichi Zhang, Yinpeng Dong, Xiao Yang, Hang Su, Jun Zhu

The mechanistic basis of data dependence and abrupt learning in an in-context classification task Gautam Reddy Nallamala

SF(DA)$^2$: Source-free Domain Adaptation Through the Lens of Data Augmentation Uiwon Hwang, Jonghyun Lee, Juhyeon Shin, Sungroh Yoon

VDT: General-purpose Video Diffusion Transformers via Mask Modeling Haoyu Lu, Guoxing Yang, Nanyi Fei, Yuqi Huo, Zhiwu Lu, Ping Luo, Mingyu Ding

NuwaDynamics: Discovering and Updating in Causal Spatio-Temporal Modeling Kun Wang, Hao Wu, Yifan Duan, Guibin Zhang, Kai Wang, Xiaojiang Peng, yu zheng, Yuxuan Liang, Yang Wang

Unpaired Image-to-Image Translation via Neural Schrödinger Bridge Beomsu Kim, Gihyun Kwon, Kwanyoung Kim, Jong Chul YE

Adversarial Causal Bayesian Optimization Scott Sussex, Pier Giuseppe Sessa, Anastasia Makarova, Andreas Krause

Bandits with Replenishable Knapsacks: the Best of both Worlds Martino Bernasconi, Matteo Castiglioni, Andrea Celli, Federico Fusco

Building Cooperative Embodied Agents Modularly with Large Language Models Hongxin Zhang, Weihua Du, Jiaming Shan, Qinhong Zhou, Yilun Du, Joshua B Tenenbaum, Tianmin Shu, Chuang Gan

Kill Two Birds with One Stone: Rethinking Data Augmentation for Deep Long-tailed Learning Binwu Wang, Pengkun Wang, Wei Xu, Xu Wang, Yudong Zhang, Kun Wang, Yang Wang

Large Language Models Are Not Robust Multiple Choice Selectors Chujie Zheng, Hao Zhou, Fandong Meng, Jie Zhou, Minlie Huang

Emergent mechanisms for long timescales depend on training curriculum and affect performance in memory tasks Sina Khajehabdollahi, Roxana Zeraati, Emmanouil Giannakakis, Tim Schäfer, Georg Martius, Anna Levina

General Stability Analysis for Zeroth-Order Optimization Algorithms Xinyue Liu, Hualin Zhang, Bin Gu, Hong Chen

On the Scalability and Memory Efficiency of Semidefinite Programs for Lipschitz Constant Estimation of Neural Networks Zi Wang, Bin Hu, Aaron Havens, Alexandre Araujo, Yang Zheng, Yudong Chen, Somesh Jha

Entropy-MCMC: Sampling from Flat Basins with Ease Bolian Li, Ruqi Zhang

$t^3$-Variational Autoencoder: Learning Heavy-tailed Data with Student's t and Power Divergence Juno Kim, Jaehyuk Kwon, Mincheol Cho, Hyunjong Lee, Joong-Ho Won

A Stable, Fast, and Fully Automatic Learning Algorithm for Predictive Coding Networks Tommaso Salvatori, Yuhang Song, Yordan Yordanov, Beren Millidge, Lei Sha, Cornelius Emde, Zhenghua Xu, Rafal Bogacz, Thomas Lukasiewicz

Online Continual Learning for Interactive Instruction Following Agents Byeonghwi Kim, Minhyuk Seo, Jonghyun Choi

Hybrid Distillation: Connecting Masked Autoencoders with Contrastive Learners Bowen Shi, XIAOPENG ZHANG, Yaoming Wang, Li Jin, Wenrui Dai, Junni Zou, Hongkai Xiong, Qi Tian

A Fast and Provable Algorithm for Sparse Phase Retrieval Jian-Feng Cai, Yu Long, Ruixue WEN, Jiaxi Ying

Aligning Relational Learning with Lipschitz Fairness Yaning Jia, Chunhui Zhang, Soroush Vosoughi

Rethinking Complex Queries on Knowledge Graphs with Neural Link Predictors Hang Yin, Zihao Wang, Yangqiu Song

Bridging Neural and Symbolic Representations with Transitional Dictionary Learning Junyan Cheng, Peter Chin

DREAM: Dual Structured Exploration with Mixup for Open-set Graph Domain Adaption Nan Yin, Mengzhu Wang, Zhenghan Chen, Li Shen, Huan Xiong, Bin Gu, Xiao Luo

Revisiting Plasticity in Visual Reinforcement Learning: Data, Modules and Training Stages Guozheng Ma, Lu Li, Sen Zhang, Zixuan Liu, Zhen Wang, Yixin Chen, Li Shen, Xueqian Wang, Dacheng Tao

Improving the Convergence of Dynamic NeRFs via Optimal Transport Sameera Ramasinghe, Violetta Shevchenko, Gil Avraham, Hisham Husain, Anton Hengel

Domain Randomization via Entropy Maximization Gabriele Tiboni, Pascal Klink, Jan Peters, Tatiana Tommasi, Carlo D'Eramo, Georgia Chalvatzaki

Understanding the Robustness of Multi-modal Contrastive Learning to Distribution Shift Yihao Xue, Siddharth Joshi, Dang Nguyen, Baharan Mirzasoleiman

DATS: Difficulty-Aware Task Sampler for Meta-Learning Physics-Informed Neural Networks Maryam Toloubidokhti, Yubo Ye, Ryan Missel, Xiajun Jiang, Nilesh Kumar, Ruby Shrestha, Linwei Wang

Efficient Backpropagation with Variance Controlled Adaptive Sampling Ziteng Wang, Jianfei Chen, Jun Zhu

Curiosity-driven Red-teaming for Large Language Models Zhang-Wei Hong, Idan Shenfeld, Johnson (Tsun-Hsuan) Wang, Yung-Sung Chuang, Aldo Pareja, James R Glass, Akash Srivastava, Pulkit Agrawal

Unveiling the Pitfalls of Knowledge Editing for Large Language Models Zhoubo Li, Ningyu Zhang, Yunzhi Yao, Mengru Wang, Xi Chen, Huajun Chen

Dictionary Contrastive Learning for Efficient Local Supervision without Auxiliary Networks Suhwan Choi, Myeongho Jeon, Yeonjung Hwang, Jeonglyul Oh, Sungjun Lim, Joonseok Lee, Myungjoo Kang

Privacy-Preserving In-Context Learning for Large Language Models Tong Wu, Ashwinee Panda, Jiachen (Tianhao) Wang, Prateek Mittal

DreamFlow: High-quality text-to-3D generation by Approximating Probability Flow Kyungmin Lee, Kihyuk Sohn, Jinwoo Shin

Structural Estimation of Partially Observed Linear Non-Gaussian Acyclic Model: A Practical Approach with Identifiability Songyao Jin, Feng Xie, Guangyi Chen, Biwei Huang, Zhengming Chen, Xinshuai Dong, Kun Zhang

AgentVerse: Facilitating Multi-Agent Collaboration and Exploring Emergent Behaviors Weize Chen, Yusheng Su, Jingwei Zuo, Cheng Yang, Chenfei Yuan, Chi-Min Chan, Heyang Yu, Yaxi Lu, Yi-Hsin Hung, Chen Qian, Yujia Qin, Xin Cong, Ruobing Xie, Zhiyuan Liu, Maosong Sun, Jie Zhou

Provable Compositional Generalization for Object-Centric Learning Thaddäus Wiedemer, Jack Brady, Alexander Panfilov, Attila Juhos, Matthias Bethge, Wieland Brendel

BroGNet: Momentum-Conserving Graph Neural Stochastic Differential Equation for Learning Brownian Dynamics Suresh Suresh, Jayadeva Jayadeva, Sayan Ranu, N. M. Anoop Krishnan

One For All: Towards Training One Graph Model For All Classification Tasks Hao Liu, Jiarui Feng, Lecheng Kong, Ningyue Liang, Dacheng Tao, Yixin Chen, Muhan Zhang

CoBIT: A Contrastive Bi-directional Image-Text Generation Model Haoxuan You, Xiaoyue Guo, Zhecan Wang, Kai-Wei Chang, Jason Baldridge, Jiahui Yu

Quantifying the Sensitivity of Inverse Reinforcement Learning to Misspecification Joar Skalse, Alessandro Abate

Prediction without Preclusion: Recourse Verification with Reachable Sets Avni Kothari, Bogdan Kulynych, Tsui-Wei Weng, Berk Ustun

Take a Step Back: Evoking Reasoning via Abstraction in Large Language Models Huaixiu Steven Zheng, Swaroop Mishra, Xinyun Chen, Heng-Tze Cheng, Ed H. Chi, Quoc V Le, Denny Zhou

EBMDock: Neural Probabilistic Protein-Protein Docking via a Differentiable Energy Model Huaijin Wu, Wei Liu, Yatao Bian, Jiaxiang Wu, Nianzu Yang, Junchi Yan

Masked Autoencoders with Multi-Window Local-Global Attention Are Better Audio Learners Sarthak Yadav, Sergios Theodoridis, Lars Kai Hansen, Zheng-Hua Tan

OpenWebMath: An Open Dataset of High-Quality Mathematical Web Text Keiran Paster, Marco Dos Santos, Zhangir Azerbayev, Jimmy Ba

Two-stage LLM Fine-tuning with Less Specialization and More Generalization Yihan Wang, Si Si, Daliang Li, Michal Lukasik, Felix Yu, Cho-Jui Hsieh, Inderjit Dhillon, Sanjiv Kumar

Safe and Robust Watermark Injection with a Single OoD Image Shuyang Yu, Junyuan Hong, Haobo Zhang, Haotao Wang, Zhangyang Wang, Jiayu Zhou

Forward $\chi^2$ Divergence Based Variational Importance Sampling Chengrui Li, Yule Wang, Weihan Li, Anqi Wu

Constrained Bi-Level Optimization: Proximal Lagrangian Value Function Approach and Hessian-free Algorithm Wei Yao, Chengming Yu, Shangzhi Zeng, Jin Zhang

Pose Modulated Avatars from Video Chunjin Song, Bastian Wandt, Helge Rhodin

A Flexible Generative Model for Heterogeneous Tabular EHR with Missing Modality Huan He, Yijie Hao, Yuanzhe Xi, Yong Chen, Bradley Malin, Joyce Ho

Uncertainty-aware Graph-based Hyperspectral Image Classification Linlin Yu, Yifei Lou, Feng Chen

Out-Of-Domain Unlabeled Data Improves Generalization seyed amir hossein saberi, Amir Najafi, Alireza Heidari, Mohammad Hosein Movasaghinia, Abolfazl Motahari, Babak HosseinKhalaj

Fiber Monte Carlo Nick Richardson, Deniz Oktay, Yaniv Ovadia, James Bowden, Ryan P Adams

RAIN: Your Language Models Can Align Themselves without Finetuning Yuhui Li, Fangyun Wei, Jinjing Zhao, Chao Zhang, Hongyang Zhang

Learning from Label Proportions: Bootstrapping Supervised Learners via Belief Propagation Shreyas Havaldar, Navodita Sharma, Shubhi Sareen, Karthikeyan Shanmugam, Aravindan Raghuveer

Understanding the Effects of RLHF on LLM Generalisation and Diversity Robert Kirk, Ishita Mediratta, Christoforos Nalmpantis, Jelena Luketina, Eric Hambro, Edward Grefenstette, Roberta Raileanu

Lipsum-FT: Robust Fine-Tuning of Zero-Shot Models Using Random Text Guidance Giung Nam, Byeongho Heo, Juho Lee

Bongard-OpenWorld: Few-Shot Reasoning for Free-form Visual Concepts in the Real World Rujie Wu, Xiaojian Ma, Zhenliang Zhang, Wei Wang, Qing Li, Song-Chun Zhu, Yizhou Wang

One-shot Active Learning Based on Lewis Weight Sampling for Multiple Deep Models Sheng-Jun Huang, Yi Li, Yiming Sun, Ying-Peng Tang

Align With Purpose: Optimize Desired Properties in CTC Models with a General Plug-and-Play Framework Eliya Segev, Maya Alroy, Ronen Katsir, Noam Wies, Ayana Shenhav, Yael Ben-Oren, David Zar, Oren Tadmor, Jacob Bitterman, Amnon Shashua, Tal Rosenwein

On the Hardness of Constrained Cooperative Multi-Agent Reinforcement Learning Ziyi Chen, Yi Zhou, Heng Huang

Defining Expertise: Applications to Treatment Effect Estimation Alihan Hüyük, Qiyao Wei, Alicia Curth, Mihaela van der Schaar

StructComp: Substituting propagation with Structural Compression in Training Graph Contrastive Learning Shengzhong Zhang, Wenjie Yang, Xinyuan Cao, Hongwei Zhang, Zengfeng Huang

Achieving Sample and Computational Efficient Reinforcement Learning by Action Space Reduction via Grouping Yining Li, Peizhong Ju, Ness Shroff

Label-Focused Inductive Bias over Latent Object Features in Visual Classification Ilmin Kang, HyounYoung Bae, Kangil Kim

A Topological Perspective on Demystifying GNN-Based Link Prediction Performance Yu Wang, Tong Zhao, Yuying Zhao, Yunchao Liu, Xueqi Cheng, Neil Shah, Tyler Derr

Generative Sliced MMD Flows with Riesz Kernels Johannes Hertrich, Christian Wald, Fabian Altekrüger, Paul Hagemann

Understanding Domain Generalization: A Noise Robustness Perspective Rui Qiao, Bryan Kian Hsiang Low

FedImpro: Measuring and Improving Client Update in Federated Learning Zhenheng Tang, Yonggang Zhang, Shaohuai Shi, Xinmei Tian, Tongliang Liu, Bo Han, Xiaowen Chu

Learning to design protein-protein interactions with enhanced generalization Anton Bushuiev, Roman Bushuiev, Petr Kouba, Anatolii Filkin, Markéta Gabrielová, Michal Gabriel, Jiri Sedlar, Tomas Pluskal, Jiri Damborsky, Stanislav Mazurenko, Josef Sivic

Quality-Diversity through AI Feedback Herbie Bradley, Andrew Dai, Hannah Teufel, Jenny Zhang, Koen Oostermeijer, Marco Bellagente, Jeff Clune, Kenneth Stanley, G. Schott, Joel Lehman

Parameter-Efficient Multi-Task Model Fusion with Partial Linearization Anke Tang, Li Shen, Yong Luo, Yibing Zhan, Han Hu, Bo Du, Yixin Chen, Dacheng Tao

RLCD: Reinforcement Learning from Contrastive Distillation for LM Alignment Kevin Yang, Dan Klein, Asli Celikyilmaz, Nanyun (Violet) Peng, Yuandong Tian

Structural Inference with Dynamics Encoding and Partial Correlation Coefficients Aoran Wang, Jun Pang

On-Policy Distillation of Language Models: Learning from Self-Generated Mistakes Rishabh Agarwal, Nino Vieillard, Yongchao Zhou, Piotr Stanczyk, Sabela Ramos Garea, Matthieu Geist, Olivier Bachem

Out-of-Variable Generalisation for Discriminative Models Siyuan Guo, Jonas Wildberger, David Ha

The Generalization Gap in Offline Reinforcement Learning Ishita Mediratta, Qingfei You, Minqi Jiang, Roberta Raileanu

Decoupling Weighing and Selecting for Integrating Multiple Graph Pre-training Tasks Tianyu Fan, Lirong Wu, Yufei Huang, Haitao Lin, Cheng Tan, Zhangyang Gao, Stan Z Li

Beyond Imitation: Leveraging Fine-grained Quality Signals for Alignment Geyang Guo, Ranchi Zhao, Tianyi Tang, Xin Zhao, Ji-Rong Wen

Neural Optimal Transport with General Cost Functionals Arip Asadulaev, Aleksandr Korotin, Vage Egiazarian, Petr Mokrov, Evgeny Burnaev

MAP IT to Visualize Representations Robert Jenssen

Space and time continuous physics simulation from partial observations Steeven Janny, Madiha Nadri, Julie Digne, Christian Wolf

Learning Thresholds with Latent Values and Censored Feedback Jiahao Zhang, Tao Lin, Weiqiang Zheng, Zhe Feng, Yifeng Teng, Xiaotie Deng

MUFFIN: Curating Multi-Faceted Instructions for Improving Instruction Following Renze Lou, Kai Zhang, Jian Xie, Yuxuan Sun, Jihyun Ahn, Hanzi XU, Yu Su, Wenpeng Yin

Leveraging Uncertainty Estimates To Improve Classifier Performance Gundeep Arora, Srujana Merugu, Anoop Saladi, Rajeev Rastogi

Language-Interfaced Tabular Oversampling via Progressive Imputation and Self-Authentication June Yong Yang, Geondo Park, Joowon Kim, Hyeongwon Jang, Eunho Yang

Transferring Labels to Solve Annotation Mismatches Across Object Detection Datasets Yuan-Hong Liao, David Acuna, Rafid Mahmood, James Lucas, Viraj Prabhu, Sanja Fidler

SweetDreamer: Aligning Geometric Priors in 2D diffusion for Consistent Text-to-3D Weiyu LI, Rui Chen, Xuelin Chen, Ping Tan

BatchPrompt: Accomplish more with less Jianzhe Lin, Maurice Diesendruck, Liang Du, Robin Abraham

Boundary Denoising for Video Activity Localization Mengmeng Xu, Mattia Soldan, Jialin Gao, Shuming Liu, Juan-Manuel Perez-Rua, Bernard Ghanem

Don't Play Favorites: Minority Guidance for Diffusion Models Soobin Um, Suhyeon Lee, Jong Chul YE

Fine-Tuned Language Models Generate Stable Inorganic Materials as Text Nate Gruver, Anuroop Sriram, Andrea Madotto, Andrew Gordon Wilson, Larry Zitnick, Zachary Ulissi

Large Language Model Cascades with Mixture of Thought Representations for Cost-Efficient Reasoning Murong Yue, Jie Zhao, Min Zhang, Liang Du, Ziyu Yao

Lewis's Signaling Game as beta-VAE For Natural Word Lengths and Segments Ryo Ueda, TADAHIRO TANIGUCHI

Beyond task performance: evaluating and reducing the flaws of large multimodal models with in-context-learning Mustafa Shukor, Alexandre Rame, Corentin Dancette, MATTHIEU CORD

An interpretable error correction method for enhancing code-to-code translation Min Xue, Artur Andrzejak, Marla Leuther

Tree Cross Attention Leo Feng, Frederick Tung, Hossein Hajimirsadeghi, Yoshua Bengio, Mohamed Osama Ahmed

A Data-Driven Measure of Relative Uncertainty for Misclassification Detection Eduardo Dadalto Câmara Gomes, Marco Romanelli, Georg Pichler, Pablo Piantanida

Bias Runs Deep: Implicit Reasoning Biases in Persona-Assigned LLMs Shashank Gupta, Vaishnavi Shrivastava, Ameet Deshpande, Ashwin Kalyan, Peter Clark, Ashish Sabharwal, Tushar Khot

Efficient Streaming Language Models with Attention Sinks Guangxuan Xiao, Yuandong Tian, Beidi Chen, Song Han, Mike Lewis

Instant3D: Fast Text-to-3D with Sparse-view Generation and Large Reconstruction Model Jiahao Li, Hao Tan, Kai Zhang, Zexiang Xu, Fujun Luan, Yinghao Xu, Yicong Hong, Kalyan Sunkavalli, Greg Shakhnarovich, Sai Bi

DataInf: Efficiently Estimating Data Influence in LoRA-tuned LLMs and Diffusion Models Yongchan Kwon, Eric Wu, Kevin Wu, James Y Zou

ODEFormer: Symbolic Regression of Dynamical Systems with Transformers Stéphane d'Ascoli, Sören Becker, Philippe Schwaller, Alexander Mathis, Niki Kilbertus

Early Stopping Against Label Noise Without Validation Data Suqin Yuan, Lei Feng, Tongliang Liu

Confronting Reward Model Overoptimization with Constrained RLHF Ted Moskovitz, Aaditya Singh, DJ Strouse, Tuomas Sandholm, Ruslan Salakhutdinov, Anca Dragan, Stephen McAleer

Energy-based Automated Model Evaluation Ru Peng, Heming Zou, Haobo Wang, Yawen Zeng, Zenan Huang, Junbo Zhao

The Effect of Intrinsic Dataset Properties on Generalization: Unraveling Learning Differences Between Natural and Medical Images Nicholas Konz, Maciej Mazurowski

Logical Languages Accepted by Transformer Encoders with Hard Attention Pablo Barcelo, Alexander Kozachinskiy, Anthony W. Lin, Vladimir Podolskii

Depthwise Hyperparameter Transfer in Residual Networks: Dynamics and Scaling Limit Blake Bordelon, Lorenzo Noci, Mufan Li, Boris Hanin, Cengiz Pehlevan

Continuous Invariance Learning Yong Lin, Fan Zhou, Lu Tan, Lintao Ma, Jianmeng Liu, Yansu HE, Yuan Yuan, Yu Liu, James Zhang, Yujiu Yang, Hao Wang

SocioDojo: Building Lifelong Analytical Agents with Real-world Text and Time Series Junyan Cheng, Peter Chin

Input-gradient space particle inference for neural network ensembles Trung Trinh, Markus Heinonen, Luigi Acerbi, Samuel Kaski

Divide and not forget: Ensemble of selectively trained experts in Continual Learning Grzegorz Rypeść, Sebastian Cygert, Valeriya Khan, Tomasz Trzcinski, Bartosz Zieliński, Bartłomiej Twardowski

LMSYS-Chat-1M: A Large-Scale Real-World LLM Conversation Dataset Lianmin Zheng, Wei-Lin Chiang, Ying Sheng, Tianle Li, Siyuan Zhuang, Zhanghao Wu, Yonghao Zhuang, Zhuohan Li, Zi Lin, Eric Xing, Joseph E Gonzalez, Ion Stoica, Hao Zhang

BayesPrompt: Prompting Large-Scale Pre-Trained Language Models on Few-shot Inference via Debiased Domain Abstraction Jiangmeng Li, Fei Song, Yifan Jin, Wenwen Qiang, Changwen Zheng, Fuchun Sun, Hui Xiong

MMD Graph Kernel: Effective Metric Learning for Graphs via Maximum Mean Discrepancy Yan Sun, Jicong Fan

Learning Energy Decompositions for Partial Inference in GFlowNets Hyosoon Jang, Minsu Kim, Sungsoo Ahn

S$2$AC: Energy-Based Reinforcement Learning with Stein Soft Actor Critic Safa Messaoud, Billel Mokeddem, Zhenghai Xue, Linsey Pang, Bo An, Haipeng Chen, Sanjay Chawla

DOS: Diverse Outlier Sampling for Out-of-Distribution Detection Wenyu Jiang, Hao Cheng, MingCai Chen, Chongjun Wang, Hongxin Wei

What Makes Good Data for Alignment? A Comprehensive Study of Automatic Data Selection in Instruction Tuning Wei Liu, Weihao Zeng, Keqing He, Yong Jiang, Junxian He

Coordinate-Aware Modulation for Neural Fields Joo Chan Lee, Daniel Rho, Seungtae Nam, Jong Hwan Ko, Eunbyung Park

CodeChain: Towards Modular Code Generation Through Chain of Self-revisions with Representative Sub-modules Hung Le, Hailin Chen, Amrita Saha, Akash Gokul, Doyen Sahoo, Shafiq Joty

UC-NERF: Neural Radiance Field for Under-Calibrated Multi-View Cameras in Autonomous Driving Kai Cheng, Xiaoxiao Long, Wei Yin, Jin Wang, Zhiqiang Wu, Yuexin Ma, Kaixuan Wang, Xiaozhi Chen, Xuejin Chen

Lie Group Decompositions for Equivariant Neural Networks Mircea Mironenco, Patrick Forré

Particle Guidance: non-I.I.D. Diverse Sampling with Diffusion Models Gabriele Corso, Yilun Xu, Valentin De Bortoli, Regina Barzilay, Tommi Jaakkola

Most discriminative stimuli for functional cell type clustering Max F. Burg, Thomas Zenkel, Michaela Vystrčilová, Jonathan Oesterle, Larissa Höfling, Konstantin F. Willeke, Jan Lause, Sarah Müller, Paul Fahey, Zhiwei Ding, Kelli Restivo, Shashwat Sridhar, Tim Gollisch, Philipp Berens, Andreas Tolias, Thomas Euler, Matthias Bethge, Alexander S Ecker

Sharpness-Aware Minimization Enhances Feature Quality via Balanced Learning Jacob Springer, Vaishnavh Nagarajan, Aditi Raghunathan

Prompt Learning with Quaternion Networks Boya Shi, Zhengqin Xu, Shuai Jia, Chao Ma

Effective Structural Encodings via Local Curvature Profiles Lukas Fesser, Melanie Weber

SE(3)-Stochastic Flow Matching for Protein Backbone Generation Joey Bose, Tara Akhound-Sadegh, Guillaume Huguet, Kilian FATRAS, Jarrid Rector-Brooks, Chenghao Liu, Andrei Nica, Maksym Korablyov, Michael Bronstein, Alexander Tong

Analyzing Feed-Forward Blocks in Transformers through the Lens of Attention Maps Goro Kobayashi, Tatsuki Kuribayashi, Sho Yokoi, Kentaro Inui

Meta-Evolve: Continuous Robot Evolution for One-to-many Policy Transfer Xingyu Liu, Deepak Pathak, DING ZHAO

The Reasonableness Behind Unreasonable Translation Capability of Large Language Model Tingchen Fu, lemao liu, Deng Cai, Guoping Huang, Shuming Shi, Rui Yan

ContextRef: Evaluating Referenceless Metrics for Image Description Generation Elisa Kreiss, Eric Zelikman, Christopher Potts, Nick Haber

CPPO: Continual Learning for Reinforcement Learning with Human Feedback Han Zhang, Yu Lei, Lin Gui, Min Yang, Yulan He, HUI WANG, Ruifeng Xu

AdaMerging: Adaptive Model Merging for Multi-Task Learning Enneng Yang, Zhenyi Wang, Li Shen, Shiwei Liu, Guibing Guo, Xingwei Wang, Dacheng Tao

SEGNO: Generalizing Equivariant Graph Neural Networks with Physical Inductive Biases Yang Liu, Jiashun Cheng, Haihong Zhao, Tingyang Xu, Peilin Zhao, Fugee Tsung, Jia Li, Yu Rong

Elucidating the design space of classifier-guided diffusion generation Jiajun Ma, Tianyang Hu, Wenjia Wang, Jiacheng Sun

TUVF: Learning Generalizable Texture UV Radiance Fields An-Chieh Cheng, Xueting Li, Sifei Liu, Xiaolong Wang

MagicDrive: Street View Generation with Diverse 3D Geometry Control Ruiyuan Gao, Kai Chen, Enze Xie, Lanqing HONG, Zhenguo Li, Dit-Yan Yeung, Qiang Xu

Online Information Acquisition: Hiring Multiple Agents Federico Cacciamani, Matteo Castiglioni, Nicola Gatti

TACTiS-2: Better, Faster, Simpler Attentional Copulas for Multivariate Time Series Arjun Ashok, Étienne Marcotte, Valentina Zantedeschi, Nicolas Chapados, Alexandre Drouin

Impact of Computation in Integral Reinforcement Learning for Continuous-Time Control Wenhan Cao, Wei Pan

fairret: a Framework for Differentiable Fairness Regularization Terms Maarten Buyl, MaryBeth Defrance, Tijl De Bie

Model Tells You What to Discard: Adaptive KV Cache Compression for LLMs Suyu Ge, Yunan Zhang, Liyuan Liu, Minjia Zhang, Jiawei Han, Jianfeng Gao

Neural SDF Flow for 3D Reconstruction of Dynamic Scenes wei mao, Richard Hartley, Mathieu Salzmann, Wei Mao

Grokking as the transition from lazy to rich training dynamics Tanishq Kumar, Blake Bordelon, Samuel Gershman, Cengiz Pehlevan

Forward Learning of Graph Neural Networks Namyong Park, Xing Wang, Antoine Simoulin, Shuai Yang, Grey Yang, Ryan Rossi, Puja Trivedi, Nesreen Ahmed

Multimodal Learning Without Labeled Multimodal Data: Guarantees and Applications Paul Liang, Chun Kai Ling, Yun Cheng, Alexander Obolenskiy, Yudong Liu, Rohan Pandey, Alex Wilf, Louis-Philippe Morency, Russ Salakhutdinov

DisenBooth: Identity-Preserving Disentangled Tuning for Subject-Driven Text-to-Image Generation Hong Chen, Yipeng Zhang, Simin Wu, Xin Wang, Xuguang Duan, Yuwei Zhou, Wenwu Zhu

Feature Collapse Thomas Laurent, James von Brecht, Xavier Bresson

MixSATGEN: Learning Graph Mixing for SAT Instance Generation Xinyan Chen, Yang Li, Runzhong Wang, Junchi Yan

Neural-Symbolic Recursive Machine for Systematic Generalization Qing Li, Yixin Zhu, Yitao Liang, Yingnian Wu, Song-Chun Zhu, Siyuan Huang

Belief-Enriched Pessimistic Q-Learning against Adversarial State Perturbations Xiaolin Sun, Zizhan Zheng

MetaGPT: Meta Programming for A Multi-Agent Collaborative Framework Sirui Hong, Mingchen Zhuge, Jonathan Chen, Xiawu Zheng, Yuheng Cheng, Jinlin Wang, Ceyao Zhang, zili wang, Steven Yau, Zijuan Lin, Liyang Zhou, Chenyu Ran, Lingfeng Xiao, Chenglin Wu, Jürgen Schmidhuber

Interpreting Robustness Proofs of Deep Neural Networks Debangshu Banerjee, Avaljot Singh, Gagandeep Singh

OWL: A Large Language Model for IT Operations Hongcheng Guo, Jian Yang, Jiaheng Liu, Liqun Yang, Linzheng Chai, Jiaqi Bai, Junran Peng, Xiaorong Hu, Chao Chen, Dongfeng Zhang, xu Shi, Tieqiao Zheng, liangfan zheng, Bo Zhang, Ke Xu, Zhoujun Li

Optimal criterion for feature learning of two-layer linear neural network in high dimensional interpolation regime Keita Suzuki, Taiji Suzuki

Cameras as Rays: Pose Estimation via Ray Diffusion Jason Zhang, Amy Lin, Moneish Kumar, Tzu-Hsuan Yang, Deva Ramanan, Shubham Tulsiani

Learning Flexible Body Collision Dynamics with Hierarchical Contact Mesh Transformer Youn-Yeol Yu, Jeongwhan Choi, Woojin Cho, Kookjin Lee, Nayong Kim, Kiseok Chang, ChangSeung Woo, ILHO KIM, SeokWoo Lee, Joon Young Yang, SOOYOUNG YOON, Noseong Park

PnP Inversion: Boosting Diffusion-based Editing with 3 Lines of Code Xuan Ju, Ailing Zeng, Yuxuan Bian, Shaoteng Liu, Qiang Xu

Batched Low-Rank Adaptation of Foundation Models Yeming Wen, Swarat Chaudhuri

MathVista: Evaluating Mathematical Reasoning of Foundation Models in Visual Contexts Pan Lu, Hritik Bansal, Tony Xia, Jiacheng Liu, Chunyuan Li, Hannaneh Hajishirzi, Hao Cheng, Kai-Wei Chang, Michel Galley, Jianfeng Gao

Bridging State and History Representations: Understanding Self-Predictive RL Tianwei Ni, Benjamin Eysenbach, Erfan Seyedsalehi, Michel Ma, Clement Gehring, Aditya Mahajan, Pierre-Luc Bacon

Making Pre-trained Language Models Great on Tabular Prediction Jiahuan Yan, Bo Zheng, Hongxia Xu, Yiheng Zhu, Danny Chen, Jimeng Sun, Jian Wu, Jintai Chen

Stable Anisotropic Regularization William Rudman, Carsten Eickhoff

NOLA: Compressing LoRA using Linear Combination of Random Basis Soroush Abbasi Koohpayegani, K L Navaneet, Parsa Nooralinejad, Soheil Kolouri, Hamed Pirsiavash

Attention-Guided Contrastive Role Representations for Multi-agent Reinforcement Learning Zican Hu, Zongzhang Zhang, Huaxiong Li, Chunlin Chen, Hongyu Ding, Zhi Wang

Can LLMs Express Their Uncertainty? An Empirical Evaluation of Confidence Elicitation in LLMs Miao Xiong, Zhiyuan Hu, Xinyang Lu, YIFEI LI, Jie Fu, Junxian He, Bryan Hooi

Constrained Decoding for Cross-lingual Label Projection Duong Le, Yang Chen, Alan Ritter, Wei Xu

An Image Is Worth 1000 Lies: Transferability of Adversarial Images across Prompts on Vision-Language Models Haochen Luo, Jindong Gu, Fengyuan Liu, Philip Torr

CADS: Unleashing the Diversity of Diffusion Models through Condition-Annealed Sampling Seyedmorteza Sadat, Jakob Buhmann, Derek Bradley, Otmar Hilliges, Romann Weber

Faithful Vision-Language Interpretation via Concept Bottleneck Models Songning Lai, Lijie Hu, Junxiao Wang, Laure Berti-Equille, Di Wang

Defining and extracting generalizable interaction primitives from DNNs Lu Chen, Siyu Lou, Benhao Huang, Quanshi Zhang

ReFusion: Improving Natural Language Understanding with Computation-Efficient Retrieval Representation Fusion Shangyu Wu, Ying Xiong, Yufei CUI, Xue Liu, Buzhou Tang, Tei-Wei Kuo, Chun Jason Xue

A Unified and General Framework for Continual Learning Zhenyi Wang, Yan Li, Li Shen, Heng Huang

Pushing Boundaries: Mixup's Influence on Neural Collapse Quinn Fisher, Haoming Meng, Vardan Papyan

Time-LLM: Time Series Forecasting by Reprogramming Large Language Models Ming Jin, Shiyu Wang, Lintao Ma, Zhixuan Chu, James Zhang, Xiaoming Shi, Pin-Yu Chen, Yuxuan Liang, Yuan-Fang Li, Shirui Pan, Qingsong Wen

Grokking as a First Order Phase Transition in Two Layer Networks Noa Rubin, Inbar Seroussi, Zohar Ringel

Fusion Is Not Enough: Single Modal Attacks on Fusion Models for 3D Object Detection Zhiyuan Cheng, Hongjun Choi, Shiwei Feng, James Liang, Guanhong Tao, Dongfang Liu, Michael Zuzak, Xiangyu Zhang

On the Generalization and Approximation Capacities of Neural Controlled Differential Equations Linus Bleistein, Agathe Guilloux

PromptAgent: Strategic Planning with Language Models Enables Expert-level Prompt Optimization Xinyuan Wang, Chenxi Li, Zhen Wang, Fan Bai, Haotian Luo, Jiayou Zhang, Nebojsa Jojic, Eric Xing, Zhiting Hu

Learning interpretable control inputs and dynamics underlying animal locomotion Thomas Soares Mullen, Marine Schimel, Guillaume Hennequin, Christian Machens, Michael B. Orger, Adrien Jouary

The All-Seeing Project: Towards Panoptic Visual Recognition and Understanding of the Open World Weiyun Wang, Min Shi, Qingyun Li, Wenhai Wang, Zhenhang Huang, Linjie Xing, Zhe Chen, Hao Li, Xizhou Zhu, Zhiguo Cao, Yushi Chen, Tong Lu, Jifeng Dai, Yu Qiao

Repeated Random Sampling for Minimizing the Time-to-Accuracy of Learning Patrik Okanovic, Roger Waleffe, Vasilis Mageirakos, Konstantinos Nikolakakis, Amin Karbasi, Dionysios Kalogerias, Nezihe Merve Gürel, Theodoros Rekatsinas

Adaptive Regret for Bandits Made Possible: Two Queries Suffice Zhou Lu, Qiuyi (Richard) Zhang, Xinyi Chen, Fred Zhang, David Woodruff, Elad Hazan

Understanding Catastrophic Forgetting in Language Models via Implicit Inference Suhas Kotha, Jacob Springer, Aditi Raghunathan

Image Clustering via the Principle of Rate Reduction in the Age of Pretrained Models Tianzhe Chu, Shengbang Tong, Tianjiao Ding, Xili Dai, Benjamin Haeffele, Rene Vidal, Yi Ma

Be Careful What You Smooth For: Label Smoothing Can Be a Privacy Shield but Also a Catalyst for Model Inversion Attacks Lukas Struppek, Dominik Hintersdorf, Kristian Kersting

Towards Meta-Pruning via Optimal Transport Alexander Theus, Olin Geimer, Friedrich Wicke, Thomas Hofmann, Sotiris Anagnostidis, Sidak Pal Singh

Fast Equilibrium of SGD in Generic Situations Zhiyuan Li, Yi Wang, Zhiren Wang

Robust Training of Federated Models with Extremely Label Deficiency Yonggang Zhang, Zhiqin Yang, Xinmei Tian, Nannan Wang, Tongliang Liu, Bo Han

Deep Generative Clustering with Multimodal Diffusion Variational Autoencoders Emanuele Palumbo, Laura Manduchi, Sonia Laguna, Daphné Chopard, Julia E Vogt

How Over-Parameterization Slows Down Gradient Descent in Matrix Sensing: The Curses of Symmetry and Initialization Nuoya Xiong, Lijun Ding, Simon Du

ConjNorm: Tractable Density Estimation for Out-of-Distribution Detection Bo Peng, Yadan Luo, Yonggang Zhang, Yixuan Li, Zhen Fang

Improving equilibrium propagation without weight symmetry through Jacobian homeostasis Axel Laborieux, Friedemann Zenke

PARL: A Unified Framework for Policy Alignment in Reinforcement Learning from Human Feedback Souradip Chakraborty, Amrit Bedi, Alec Koppel, Huazheng Wang, Dinesh Manocha, Mengdi Wang, Furong Huang

Unified Human-Scene Interaction via Prompted Chain-of-Contacts Zeqi Xiao, Tai Wang, Jingbo Wang, Jinkun Cao, Wenwei Zhang, Bo DAI, Dahua Lin, Jiangmiao Pang

Mixture of Weak and Strong Experts on Graphs Hanqing Zeng, Hanjia Lyu, Diyi Hu, Yinglong Xia, Jiebo Luo

Less or More From Teacher: Exploiting Trilateral Geometry For Knowledge Distillation Chengming Hu, Haolun Wu, Xuan Li, Chen Ma, Xi Chen, Boyu Wang, Jun Yan, Xue Liu

Hiding in Plain Sight: Disguising Data Stealing Attacks in Federated Learning Kostadin Garov, Dimitar I. Dimitrov, Nikola Jovanović, Martin Vechev

Goodhart's Law in Reinforcement Learning Jacek Karwowski, Oliver Hayman, Xingjian Bai, Klaus Kiendlhofer, Charlie Griffin, Joar Skalse

UniAdapter: Unified Parameter-Efficient Transfer Learning for Cross-modal Modeling Haoyu Lu, Yuqi Huo, Guoxing Yang, Zhiwu Lu, Wei Zhan, Masayoshi Tomizuka, Mingyu Ding

Abstractors and relational cross-attention: An inductive bias for explicit relational reasoning in Transformers Awni Altabaa, Taylor Webb, Jonathan Cohen, John Lafferty

Boosting Vanilla Lightweight Vision Transformers via Re-parameterization Zhentao Tan, Xiaodan Li, Yue Wu, Qi Chu, Le Lu, Nenghai Yu, Jieping Ye

Multilingual Jailbreak Challenges in Large Language Models Yue Deng, Wenxuan Zhang, Sinno Jialin Pan, Lidong Bing

Octavius: Mitigating Task Interference in MLLMs via LoRA-MoE Zeren Chen, ziqin wang, zhen wang, Huayang Liu, Zhenfei Yin, Si Liu, Lyu Sheng, Wanli Ouyang, Jing Shao

Discovering modular solutions that generalize compositionally Simon Schug, Seijin Kobayashi, Yassir Akram, Maciej Wołczyk, Alexandra M Proca, Johannes von Oswald, Razvan Pascanu, Joao Sacramento, Angelika Steger

LLMCarbon: Modeling the End-to-End Carbon Footprint of Large Language Models Ahmad Faiz, Sotaro Kaneda, Ruhan Wang, Rita Osi, Prateek Sharma, Fan Chen, Lei Jiang

Enabling Efficient Equivariant Operations in the Fourier Basis via Gaunt Tensor Products Shengjie Luo, Tianlang Chen, Aditi Krishnapriyan

Diving Segmentation Model into Pixels Chen Gan, Zihao Yin, Kelei He, Yang Gao, Junfeng Zhang

Self-Guided Masked Autoencoders for Domain-Agnostic Self-Supervised Learning Johnathan Xie, Yoonho Lee, Annie Chen, Chelsea Finn

Fast-DetectGPT: Efficient Zero-Shot Detection of Machine-Generated Text via Conditional Probability Curvature Guangsheng Bao, Yanbin Zhao, Zhiyang Teng, Linyi Yang, Yue Zhang

Learning to solve Class-Constrained Bin Packing Problems via Encoder-Decoder Model Hanni Cheng, Ya Cong, Weihao Jiang, Shiliang Pu

From Latent Graph to Latent Topology Inference: Differentiable Cell Complex Module Claudio Battiloro, Indro Spinelli, Lev Telyatinkov, Michael Bronstein, Simone Scardapane, Paolo Di Lorenzo

Fantastic Gains and Where to Find Them: On the Existence and Prospect of General Knowledge Transfer between Any Pretrained Model Karsten Roth, Lukas Thede, A. Sophia Koepke, Oriol Vinyals, Olivier Henaff, Zeynep Akata

The Unlocking Spell on Base LLMs: Rethinking Alignment via In-Context Learning Bill Yuchen Lin, Abhilasha Ravichander, Ximing Lu, Nouha Dziri, Melanie Sclar, Khyathi Chandu, Chandra Bhagavatula, Yejin Choi

Outliers with Opposing Signals Have an Outsized Effect on Neural Network Optimization Elan Rosenfeld, Andrej Risteski

Tractable Probabilistic Graph Representation Learning with Graph-Induced Sum-Product Networks Federico Errica, Mathias Niepert

Teaching Arithmetic to Small Transformers Nayoung Lee, Kartik Sreenivasan, Jason Lee, Kangwook Lee, Dimitris Papailiopoulos

Quantifying Language Models' Sensitivity to Spurious Features in Prompt Design or: How I learned to start worrying about prompt formatting Melanie Sclar, Yejin Choi, Yulia Tsvetkov, Alane Suhr

A Benchmark Study on Calibration Linwei Tao, Younan Zhu, Haolan Guo, Minjing Dong, Chang Xu

Würstchen: An Efficient Architecture for Large-Scale Text-to-Image Diffusion Models Pablo Pernías, Dominic Rampas, Mats L. Richter, Christopher Pal, Marc Aubreville

Towards Robust Multi-Modal Reasoning via Model Selection Xiangyan Liu, Rongxue LI, Wei Ji, Tao Lin

SILO Language Models: Isolating Legal Risk In a Nonparametric Datastore Sewon Min, Suchin Gururangan, Eric Wallace, Weijia Shi, Hannaneh Hajishirzi, Noah Smith, Luke Zettlemoyer

The Joint Effect of Task Similarity and Overparameterization on Catastrophic Forgetting — An Analytical Model Daniel Goldfarb, Itay Evron, Nir Weinberger, Daniel Soudry, Paul Hand

Self-supervised Pocket Pretraining via Protein Fragment-Surroundings Alignment Bowen Gao, Yinjun JIA, Yuanle Mo, Yuyan Ni, Wei-Ying Ma, Zhi-Ming Ma, Yanyan Lan

Neuron-Enhanced AutoEncoder Matrix Completion and Collaborative Filtering: Theory and Practice Jicong Fan, Rui Chen, Zhao Zhang, Chris Ding

Learning to Make Adherence-aware Advice Guanting Chen, Xiaocheng Li, Chunlin Sun, Hanzhao Wang

Neural structure learning with stochastic differential equations Benjie Wang, Joel Jennings, Wenbo Gong

The Human-AI Substitution game: active learning from a strategic labeler Tom Yan, Chicheng Zhang

ReLU Strikes Back: Exploiting Activation Sparsity in Large Language Models Iman Mirzadeh, Keivan Alizadeh-Vahid, Sachin Mehta, Carlo C del Mundo, Oncel Tuzel, Golnoosh Samei, Mohammad Rastegari, Mehrdad Farajtabar

Pushing Mixture of Experts to the Limit: Extremely Parameter Efficient MoE for Instruction Tuning Ted Zadouri, Ahmet Üstün, Arash Ahmadian, Beyza Ermis, Acyr Locatelli, Sara Hooker

Multi-resolution HuBERT: Multi-resolution Speech Self-Supervised Learning with Masked Unit Prediction Jiatong Shi, Hirofumi Inaguma, Xutai Ma, Ilia Kulikov, Anna Sun

Finetuning Text-to-Image Diffusion Models for Fairness Xudong Shen, Chao Du, Tianyu Pang, Min Lin, Yongkang Wong, Mohan Kankanhalli

SemiReward: A General Reward Model for Semi-supervised Learning Siyuan Li, Weiyang Jin, Zedong Wang, Fang Wu, Zicheng Liu, Cheng Tan, Stan Z Li

Quantifying the Plausibility of Context Reliance in Neural Machine Translation Gabriele Sarti, Grzegorz Chrupała, Malvina Nissim, Arianna Bisazza

Sharpness-Aware Data Poisoning Attack Pengfei He, Han Xu, Jie Ren, Yingqian Cui, Shenglai Zeng, Hui Liu, Charu Aggarwal, Jiliang Tang

Seeking Neural Nuggets: Knowledge Transfer in Large Language Models from a Parametric Perspective Ming Zhong, Chenxin An, Weizhu Chen, Jiawei Han, Pengcheng He

Evaluating Representation Learning on the Protein Structure Universe Arian Jamasb, Alex Morehead, Chaitanya Joshi, Zuobai Zhang, Kieran Didi, Simon Mathis, Charles Harris, Jian Tang, Jianlin Cheng, Pietro Lio, Tom Blundell

MetaCoCo: A New Few-Shot Classification Benchmark with Spurious Correlation Min Zhang, Haoxuan Li, Fei Wu, Kun Kuang

Understanding Convergence and Generalization in Federated Learning through Feature Learning Theory Wei Huang, Ye Shi, Zhongyi Cai, Taiji Suzuki

InstructScene: Instruction-Driven 3D Indoor Scene Synthesis with Semantic Graph Prior Chenguo Lin, Yadong MU

Vocos: Closing the gap between time-domain and Fourier-based neural vocoders for high-quality audio synthesis Hubert Siuzdak

Toward effective protection against diffusion-based mimicry through score distillation Haotian Xue, Chumeng Liang, Xiaoyu Wu, Yongxin Chen

Expressivity of ReLU-Networks under Convex Relaxations Maximilian Baader, Mark N Müller, Yuhao Mao, Martin Vechev

Flag Aggregator: Scalable Distributed Training under Failures and Augmented Losses using Convex Optimization Hamidreza Almasi, Harsh Mishra, Balajee Vamanan, Sathya N. Ravi

Removing Biases from Molecular Representations via Information Maximization Chenyu Wang, Sharut Gupta, Caroline Uhler, Tommi Jaakkola

On Diffusion Modeling for Anomaly Detection Victor Livernoche, Vineet Jain, Yashar Hezaveh, Siamak Ravanbakhsh

Self-Supervised High Dynamic Range Imaging with Multi-Exposure Images in Dynamic Scenes Zhilu Zhang, Haoyu Wang, Shuai Liu, Xiaotao Wang, LEI LEI, Wangmeng Zuo

Generative Modeling with Phase Stochastic Bridge Tianrong Chen, Jiatao Gu, Laurent Dinh, Evangelos Theodorou, Joshua Susskind, Shuangfei Zhai

Causality-Inspired Spatial-Temporal Explanations for Dynamic Graph Neural Networks Kesen Zhao, Liang Zhang

ED-NeRF: Efficient Text-Guided Editing of 3D Scene With Latent Space NeRF Jangho Park, Gihyun Kwon, Jong Chul YE

On the hardness of learning under symmetries Bobak Kiani, Thien Le, Hannah Lawrence, Stefanie Jegelka, Melanie Weber

Information Retention via Learning Supplemental Features Zhipeng Xie, Yahe Li

Policy Rehearsing: Training Generalizable Policies for Reinforcement Learning Chengxing Jia, Chen-Xiao Gao, Hao Yin, Fuxiang Zhang, XiongHui Chen, Tian Xu, Lei Yuan, Zongzhang Zhang, Zhi-Hua Zhou, Yang Yu

SEAL: A Framework for Systematic Evaluation of Real-World Super-Resolution Wenlong Zhang, Xiaohui Li, Xiangyu Chen, Xiaoyun Zhang, Yu Qiao, Xiao-Ming Wu, Chao Dong

Consistent Multi-Class Classification from Multiple Unlabeled Datasets Zixi Wei, Senlin Shu, Yuzhou Cao, Hongxin Wei, Bo An, Lei Feng

R&B: Region and Boundary Aware Zero-shot Grounded Text-to-image Generation Jiayu Xiao, Henglei Lv, Liang Li, Shuhui Wang, Qingming Huang

BadEdit: Backdooring Large Language Models by Model Editing Yanzhou Li, Tianlin Li, Kangjie Chen, Jian Zhang, Shangqing Liu, Wenhan Wang, Tianwei Zhang, Yang Liu

DreamSmooth: Improving Model-based Reinforcement Learning via Reward Smoothing Vint Lee, Pieter Abbeel, Youngwoon Lee

PolyGCL: GRAPH CONTRASTIVE LEARNING via Learnable Spectral Polynomial Filters Jingyu Chen, Runlin Lei, Zhewei Wei

FairerCLIP: Debiasing CLIP's Zero-Shot Predictions using Functions in RKHSs Sepehr Dehdashtian, Lan Wang, Vishnu Boddeti

Unraveling the Enigma of Double Descent: An In-depth Analysis through the Lens of Learned Feature Space Yufei Gu, Xiaoqing Zheng, Tomaso Aste

Efficiently Computing Similarities to Private Datasets Arturs Backurs, Zinan Lin, Sepideh Mahabadi, Sandeep Silwal, Jakub Tarnawski

Navigating the Design Space of Equivariant Diffusion-Based Generative Models for De Novo 3D Molecule Generation Tuan Le, Julian Cremer, Frank Noe, Djork-Arné Clevert, Kristof T. Schütt

Language-Informed Visual Concept Learning Sharon Lee, Yunzhi Zhang, Shangzhe Wu, Jiajun Wu

FITS: Modeling Time Series with $10k$ Parameters Zhijian Xu, Ailing Zeng, Qiang Xu

ConR: Contrastive Regularizer for Deep Imbalanced Regression Mahsa Keramati, Lili Meng, R. Evans

GIO: Gradient Information Optimization for Training Dataset Selection Dante Everaert, Christopher Potts

Improving Intrinsic Exploration by Creating Stationary Objectives Roger Creus Castanyer, Joshua Romoff, Glen Berseth

Stochastic Gradient Descent for Gaussian Processes Done Right Jihao Andreas Lin, Shreyas Padhy, Javier Antorán, Austin Tripp, Alexander Terenin, Csaba Szepesvari, José Miguel Hernández Lobato, David Janz

Private Zeroth-Order Nonsmooth Nonconvex Optimization Qinzi Zhang, Hoang Tran, Ashok Cutkosky

Simple Minimax Optimal Byzantine Robust Algorithm for Nonconvex Objectives with Uniform Gradient Heterogeneity Tomoya Murata, Kenta Niwa, Takumi Fukami, Iifan Tyou

Is This the Subspace You Are Looking for? An Interpretability Illusion for Subspace Activation Patching Aleksandar Makelov, Georg Lange, Atticus Geiger, Neel Nanda

Eureka: Human-Level Reward Design via Coding Large Language Models Yecheng Jason Ma, William Liang, Guanzhi Wang, De-An Huang, Osbert Bastani, Dinesh Jayaraman, Yuke Zhu, Jim Fan, anima anandkumar

FOSI: Hybrid First and Second Order Optimization Hadar Sivan, Moshe Gabel, Assaf Schuster

Delta-AI: Local objectives for amortized inference in sparse graphical models Jean-Pierre Falet, Hae Beom Lee, Nikolay Malkin, Chen Sun, Dragos Secrieru, Dinghuai Zhang, Guillaume Lajoie, Yoshua Bengio

Select to Perfect: Imitating desired behavior from large multi-agent data Tim Franzmeyer, Edith Elkind, Philip Torr, Jakob Foerster, Joao F. Henriques

Understanding Augmentation-based Self-Supervised Representation Learning via RKHS Approximation and Regression Runtian Zhai, Bingbin Liu, Andrej Risteski, Zico Kolter, Pradeep K Ravikumar

Task structure and nonlinearity jointly determine learned representational geometry Matteo Alleman, Jack Lindsey, Stefano Fusi

Empirical Analysis of Model Selection for Heterogeneous Causal Effect Estimation Divyat Mahajan, Ioannis Mitliagkas, Brady Neal, Vasilis Syrgkanis

Vision-Language Foundation Models as Effective Robot Imitators Xinghang Li, Minghuan Liu, Hanbo Zhang, Cunjun Yu, Jie Xu, Hongtao Wu, Chilam Cheang, Ya Jing, Weinan Zhang, Huaping Liu, Hang Li, Tao Kong

Bayes Conditional Distribution Estimation for Knowledge Distillation Based on Conditional Mutual Information Linfeng Ye, Shayan Mohajer Hamidi, Renhao Tan, EN-HUI YANG

Convolution Meets LoRA: Parameter Efficient Finetuning for Segment Anything Model Zihan Zhong, Zhiqiang Tang, Tong He, Haoyang Fang, Chun Yuan

Bounding Box Stability against Feature Dropout Reflects Detector Generalization across Environments Yang Yang, Wenhai Wang, Zhe Chen, Jifeng Dai, Liang Zheng

Unlocking the Power of Representations in Long-term Novelty-based Exploration Alaa Saade, Steven Kapturowski, Daniele Calandriello, Charles Blundell, Pablo Sprechmann, Leopoldo Sarra, Oliver Groth, Michal Valko, Bilal Piot

Role of Locality and Weight Sharing in Image-Based Tasks: A Sample Complexity Separation between CNNs, LCNs, and FCNs Aakash Sunil Lahoti, Stefani Karp, Ezra Winston, Aarti Singh, Yuanzhi Li

Deep SE(3)-Equivariant Geometric Reasoning for Precise Placement Tasks Ben Eisner, Yi Yang, Todor Davchev, Mel Vecerik, Jonathan Scholz, David Held

Separating common from salient patterns with Contrastive Representation Learning Robin Louiset, Edouard Duchesnay, Grigis Antoine, Pietro Gori

AMAGO: Scalable In-Context Reinforcement Learning for Adaptive Agents Jake Grigsby, Jim Fan, Yuke Zhu

Gradual Domain Adaptation via Gradient Flow Zhan ZHUANG, Yu Zhang, Ying Wei

Mastering Symbolic Operations: Augmenting Language Models with Compiled Neural Networks Yixuan Weng, Minjun Zhu, Fei Xia, Bin Li, Shizhu He, Kang Liu, Jun Zhao

Modeling state-dependent communication between brain regions with switching nonlinear dynamical systems Orren Karniol-Tambour, David Zoltowski, E. Mika Diamanti, Lucas Pinto, Carlos Brody, David Tank, Jonathan Pillow

Identifying the Risks of LM Agents with an LM-Emulated Sandbox Yangjun Ruan, Honghua Dong, Andrew Wang, Silviu Pitis, Yongchao Zhou, Jimmy Ba, Yann Dubois, Chris Maddison, Tatsunori Hashimoto

Navigating Text-To-Image Customization: From LyCORIS Fine-Tuning to Model Evaluation Shih-Ying Yeh, Yu-Guan Hsieh, Zhidong Gao, Bernard Yang, Giyeong Oh, Yanmin Gong

On the Variance of Neural Network Training with respect to Test Sets and Distributions Keller Jordan

Demystifying Embedding Spaces using Large Language Models Guy Tennenholtz, Yinlam Chow, ChihWei Hsu, Jihwan Jeong, Lior Shani, Azamat Tulepbergenov, Deepak Ramachandran, Martin Mladenov, Craig Boutilier

WizardCoder: Empowering Code Large Language Models with Evol-Instruct Ziyang Luo, Can Xu, Pu Zhao, Qingfeng Sun, Xiubo Geng, Wenxiang Hu, Chongyang Tao, Jing Ma, Qingwei Lin, Daxin Jiang

Candidate Label Set Pruning: A Data-centric Perspective for Deep Partial-label Learning Shuo He, Chaojie Wang, Guowu Yang, Lei Feng

Causal Structure Recovery with Latent Variables under Milder Distributional and Graphical Assumptions Xiuchuan Li, Kun Zhang, Tongliang Liu

Faithful and Efficient Explanations for Neural Networks via Neural Tangent Kernel Surrogate Models Andrew Engel, Zhichao Wang, Natalie Frank, Ioana Dumitriu, Sutanay Choudhury, Anand Sarwate, Tony Chiang

Function-space Parameterization of Neural Networks for Sequential Learning Aidan Scannell, Riccardo Mereu, Paul Chang, Ella Tamir, Joni Pajarinen, Arno Solin

Exploring the cloud of feature interaction scores in a Rashomon set Sichao Li, Rong Wang, Quanling Deng, Amanda Barnard

Deep Reinforcement Learning for Modelling Protein Complexes Ziqi Gao, Tao Feng, Jiaxuan You, Chenyi Zi, Yan Zhou, Chen Zhang, Jia Li

Exposing Text-Image Inconsistency Using Diffusion Models Mingzhen Huang, Shan Jia, Zhou Zhou, Yan Ju, Jialing Cai, Siwei Lyu

On the Effect of Batch Size in Byzantine-Robust Distributed Learning Yi-Rui Yang, Chang-Wei Shi, Wu-Jun Li

Language Model Decoding as Direct Metrics Optimization Haozhe Ji, Pei Ke, Hongning Wang, Minlie Huang

Distributional Preference Learning: Understanding and Accounting for Hidden Context in RLHF Anand Siththaranjan, Cassidy Laidlaw, Dylan Hadfield-Menell

Improving Non-Transferable Representation Learning by Harnessing Content and Style Ziming Hong, Zhenyi Wang, Li Shen, Yu Yao, Zhuo Huang, Shiming Chen, chuanwu yang, Mingming Gong, Tongliang Liu

Robustness of AI-Image Detectors: Fundamental Limits and Practical Attacks Mehrdad Saberi, Vinu Sankar Sadasivan, Keivan Rezaei, Aounon Kumar, Atoosa Chegini, Wenxiao Wang, Soheil Feizi

Adaptive Window Pruning for Efficient Local Motion Deblurring Haoying Li, Jixin Zhao, Shangchen Zhou, Huajun Feng, Chongyi Li, Chen Change Loy

Generative Judge for Evaluating Alignment Junlong Li, Shichao Sun, Weizhe Yuan, Run-Ze Fan, hai zhao, Pengfei Liu

Exploring the Promise and Limits of Real-Time Recurrent Learning Kazuki Irie, Anand Gopalakrishnan, Jürgen Schmidhuber

Learning to Embed Time Series Patches Independently Seunghan Lee, Taeyoung Park, Kibok Lee

Graph Generation with $K^2$-trees Yunhui Jang, Dongwoo Kim, Sungsoo Ahn

Improved algorithm and bounds for successive projection Jiashun Jin, Tracy Ke, Gabriel Moryoussef, Jiajun Tang, Jingming Wang

SCHEMA: State CHangEs MAtter for Procedure Planning in Instructional Videos Yulei Niu, Wenliang Guo, Long Chen, Xudong Lin, Shih-Fu Chang

SyncDreamer: Generating Multiview-consistent Images from a Single-view Image Yuan Liu, Cheng Lin, Zijiao Zeng, Xiaoxiao Long, Lingjie Liu, Taku Komura, Wenping Wang

Efficient and Scalable Graph Generation through Iterative Local Expansion Andreas Bergmeister, Karolis Martinkus, Nathanaël Perraudin, Roger Wattenhofer

MOFI: Learning Image Representations from Noisy Entity Annotated Images Wentao Wu, Aleksei Timofeev, Chen Chen, Bowen Zhang, Kun Duan, Shuangning Liu, Yantao Zheng, Jonathon Shlens, Xianzhi Du, Yinfei Yang

Chameleon: Increasing Label-Only Membership Leakage with Adaptive Poisoning Harsh Chaudhari, Giorgio Severi, Alina Oprea, Jonathan Ullman

Repelling Random Walks Isaac Reid, Eli Berger, Krzysztof Choromanski, Adrian Weller

Inverse Approximation Theory for Nonlinear Recurrent Neural Networks Shida Wang, Zhong Li, Qianxiao Li

SpikePoint: An Efficient Point-based Spiking Neural Network for Event Cameras Action Recognition Hongwei Ren, Yue ZHOU, Xiaopeng LIN, Yulong Huang, Haotian FU, Jie Song, Bojun Cheng

Scalable and Effective Implicit Graph Neural Networks on Large Graphs Juncheng Liu, Bryan Hooi, Kenji Kawaguchi, Yiwei Wang, Chaosheng Dong, Xiaokui Xiao

UniTabE: A Universal Pretraining Protocol for Tabular Foundation Model in Data Science Yazheng Yang, Yuqi Wang, Guang Liu, Ledell Wu, Qi Liu

Mathematical Justification of Hard Negative Mining via Isometric Approximation Theorem Albert Xu, Jhih-Yi Hsieh, Bhaskar Vundurthy, Nithya Kemp, Eliana Cohen, Lu Li, Howie Choset

Think before you speak: Training Language Models With Pause Tokens Sachin Goyal, Ziwei Ji, Ankit Singh Rawat, Aditya Krishna Menon, Sanjiv Kumar, Vaishnavh Nagarajan

Set Learning for Accurate and Calibrated Models Lukas Muttenthaler, Robert A Vandermeulen, Qiuyi (Richard) Zhang, Thomas Unterthiner, Klaus R Muller

Stochastic Controlled Averaging for Federated Learning with Communication Compression Xinmeng Huang, Ping Li, Xiaoyun Li

CivRealm: A Learning and Reasoning Odyssey in Civilization for Decision-Making Agents Siyuan Qi, Shuo Chen, Yexin Li, Xiangyu Kong, Junqi Wang, Bangcheng Yang, pring wong, Yifan Zhong, Xiaoyuan Zhang, Zhaowei Zhang, Nian Liu, Yaodong Yang, Song-Chun Zhu

A Variational Perspective on Solving Inverse Problems with Diffusion Models Morteza Mardani, Jiaming Song, Jan Kautz, Arash Vahdat

Lagrangian Flow Networks for Conservation Laws Fabricio Arend Torres, Marcello Negri, Marco Inversi, Jonathan Aellen, Volker Roth

Unveiling and Manipulating Prompt Influence in Large Language Models Zijian Feng, Hanzhang Zhou, ZIXIAO ZHU, Junlang Qian, Kezhi Mao

Coeditor: Leveraging Repo-level Diffs for Code Auto-editing Jiayi Wei, Greg Durrett, Isil Dillig

CLIP the Bias: How Useful is Balancing Data in Multimodal Learning? Ibrahim Alabdulmohsin, Xiao Wang, Andreas Steiner, Priya Goyal, Alexander D'Amour, Xiaohua Zhai

Decoupled Marked Temporal Point Process using Neural Ordinary Differential Equations Yujee Song, Donghyun LEE, Rui Meng, Won Hwa Kim

OmniControl: Control Any Joint at Any Time for Human Motion Generation Yiming Xie, Varun Jampani, Lei Zhong, Deqing Sun, Huaizu Jiang

I-PHYRE: Interactive Physical Reasoning Shiqian Li, Kewen Wu, Chi Zhang, Yixin Zhu

Protein Discovery with Discrete Walk-Jump Sampling Nathan Frey, Dan Berenberg, Karina Zadorozhny, Joseph Kleinhenz, Julien Lafrance-Vanasse, Isidro Hotzel, Yan Wu, Stephen Ra, Richard Bonneau, Kyunghyun Cho, Andreas Loukas, Vladimir Gligorijevic, Saeed Saremi

Stabilizing Contrastive RL: Techniques for Robotic Goal Reaching from Offline Data Chongyi Zheng, Benjamin Eysenbach, Homer Walke, Patrick Yin, Kuan Fang, Ruslan Salakhutdinov, Sergey Levine

Adaptive Rational Activations to Boost Deep Reinforcement Learning Quentin Delfosse, Patrick Schramowski, Martin Mundt, Alejandro Molina Ramirez, Kristian Kersting

BadChain: Backdoor Chain-of-Thought Prompting for Large Language Models Zhen Xiang, Fengqing Jiang, Zidi Xiong, Bhaskar Ramasubramanian, Radha Poovendran, Bo Li

Unifying Feature and Cost Aggregation with Transformers for Semantic and Visual Correspondence Sunghwan Hong, Seokju Cho, Seungryong Kim, Stephen Lin

Searching for High-Value Molecules Using Reinforcement Learning and Transformers Raj Ghugare, Santiago Miret, Adriana Hugessen, mariano Phielipp, Glen Berseth

Enhancing Small Medical Learners with Privacy-preserving Contextual Prompting xinlu zhang, Shiyang Li, Xianjun Yang, Chenxin Tian, Yao Qin, Linda Petzold

Time-Varying Propensity Score to Bridge the Gap between the Past and Present Rasool Fakoor, Jonas Mueller, Zachary Lipton, Pratik A Chaudhari, Alex Smola

Scalable Language Model with Generalized Continual Learning Bohao PENG, Zhuotao Tian, Shu Liu, Ming-Chang Yang, Jiaya Jia

From Sparse to Soft Mixtures of Experts Joan Puigcerver, Carlos Riquelme Ruiz, Basil Mustafa, Neil Houlsby

Vision-Language Models are Zero-Shot Reward Models for Reinforcement Learning Juan Rocamonde, Victoriano Montesinos, Elvis Nava, Ethan Perez, David Lindner

Video Decomposition Prior: Editing Videos Layer by Layer Gaurav Shrivastava, Ser-Nam Lim, Abhinav Shrivastava

FreeReg: Image-to-Point Cloud Registration Leveraging Pretrained Diffusion Models and Monocular Depth Estimators Haiping Wang, Yuan Liu, Bing WANG, YUJING SUN, Zhen Dong, Wenping Wang, Bisheng Yang

Tangent Transformers for Composition,Privacy and Removal Tian Yu Liu, Aditya Golatkar, Stefano Soatto

General Graph Random Features Isaac Reid, Krzysztof Choromanski, Eli Berger, Adrian Weller

CAMBranch: Contrastive Learning with Augmented MILPs for Branching Jiacheng Lin, Meng XU, Zhihua Xiong, Huangang Wang

Demonstration-Regularized RL Daniil Tiapkin, Denis Belomestny, Daniele Calandriello, Eric Moulines, Aleksei Naumov, Pierre Perrault, Michal Valko, Pierre Ménard

Sum-Product-Set Networks: Deep Tractable Models for Tree-Structured Graphs Milan Papez, Martin Rektoris, Vaclav Smidl, Tomáš Pevný

Can Large Language Models Infer Causation from Correlation? Zhijing Jin, Jiarui Liu, Zhiheng LYU, spencer poff, Mrinmaya Sachan, Rada Mihalcea, Mona Diab, David Ha

Towards Understanding Factual Knowledge of Large Language Models Xuming Hu, Junzhe Chen, Xiaochuan Li, Yufei Guo, Lijie Wen, Philip Yu, Zhijiang Guo

Locality-Aware Graph Rewiring in GNNs Federico Barbero, Ameya Velingker, Amin Saberi, Michael Bronstein, Francesco Di Giovanni

Temporal Generalization Estimation in Evolving Graphs Bin Lu, Tingyan Ma, Xiaoying Gan, Xinbing Wang, Yunqiang Zhu, Chenghu Zhou, Shiyu Liang

FedHyper: A Universal and Robust Learning Rate Scheduler for Federated Learning with Hypergradient Descent Ziyao Wang, Jianyu Wang, Ang Li

DAFA: Distance-Aware Fair Adversarial Training Hyungyu Lee, Saehyung Lee, Hyemi Jang, Junsung Park, Ho Bae, Sungroh Yoon

Learning Energy-Based Models by Cooperative Diffusion Recovery Likelihood yaxuan zhu, Jianwen Xie, Yingnian Wu, Ruiqi Gao

A Hard-to-Beat Baseline for Training-free CLIP-based Adaptation Zhengbo Wang, Jian Liang, Lijun Sheng, Ran He, Zilei Wang, Tieniu Tan

A Precise Characterization of SGD Stability Using Loss Surface Geometry Gregory Dexter, Borja Ocejo, Sathiya Keerthi, Aman Gupta, Ayan Acharya, Rajiv Khanna

Enhancing Tail Performance in Extreme Classifiers by Label Variance Reduction Anirudh Buvanesh, Rahul Chand, Jatin Prakash, Bhawna Paliwal, Mudit Dhawan, Neelabh Madan, Deepesh Hada, Vidit Jain, Sonu Mehta, Yashoteja Prabhu, Manish Gupta, Ramachandran Ramjee, Manik Varma

Proper Laplacian Representation Learning Diego Gomez, Michael Bowling, Marlos C. Machado

Random Sparse Lifts: Construction, Analysis and Convergence of finite sparse networks David Robin, Kevin Scaman, marc lelarge

Generative Learning for Solving Non-Convex Problem with Multi-Valued Input-Solution Mapping Enming Liang, Minghua Chen

Tuning LayerNorm in Attention: Towards Efficient Multi-Modal LLM Finetuning Bingchen Zhao, Haoqin Tu, Chen Wei, Jieru Mei, Cihang Xie

SRL: Scaling Distributed Reinforcement Learning to Over Ten Thousand Cores Zhiyu Mei, Wei Fu, Jiaxuan Gao, Guangju Wang, Huanchen Zhang, Yi Wu

MEND: Meta Demonstration Distillation for Efficient and Effective In-Context Learning Yichuan Li, Xiyao Ma, Sixing Lu, Kyumin Lee, Xiaohu Liu, Chenlei Guo

Bayesian Coreset Optimization for Personalized Federated Learning Prateek Chanda, Shrey Modi, Ganesh Ramakrishnan

Feature emergence via margin maximization: case studies in algebraic tasks Depen Morwani, Benjamin Edelman, Costin-Andrei Oncescu, Rosie Zhao, Sham Kakade

Weakly-supervised Audio Separation via Bi-modal Semantic Similarity Tanvir Mahmud, Saeed Amizadeh, Kazuhito Koishida, Diana Marculescu

Stabilizing Backpropagation Through Time to Learn Complex Physics Patrick Schnell, Nils Thuerey

Embarrassingly Simple Dataset Distillation Yunzhen Feng, Shanmukha Ramakrishna Vedantam, Julia Kempe

Neural Spectral Methods: Self-supervised learning in the spectral domain Yiheng Du, Nithin Chalapathi, Aditi Krishnapriyan

ZipIt! Merging Models from Different Tasks without Training George Stoica, Daniel Bolya, Jakob Bjorner, Pratik Ramesh, Taylor Hearn, Judy Hoffman

CIFAR-10-Warehouse: Broad and More Realistic Testbeds in Model Generalization Analysis Xiaoxiao Sun, Xingjian Leng, Zijian Wang, Yang Yang, Zi Huang, Liang Zheng

ODICE: Revealing the Mystery of Distribution Correction Estimation via Orthogonal-gradient Update Liyuan Mao, Haoran Xu, Weinan Zhang, Xianyuan Zhan

Long-tailed Diffusion Models with Oriented Calibration Tianjiao Zhang, Huangjie Zheng, Jiangchao Yao, Xiangfeng Wang, Mingyuan Zhou, Ya Zhang, Yanfeng Wang

Transformer Fusion with Optimal Transport Moritz Imfeld, Jacopo Graldi, Marco Giordano, Thomas Hofmann, Sotiris Anagnostidis, Sidak Pal Singh

Class Probability Matching with Calibrated Networks for Label Shift Adaption Hongwei Wen, Annika Betken, Hanyuan Hang

FasterViT: Fast Vision Transformers with Hierarchical Attention Ali Hatamizadeh, Greg Heinrich, Hongxu Yin, Andrew Tao, Jose M. Alvarez, Jan Kautz, Pavlo Molchanov

Few-Shot Detection of Machine-Generated Text using Style Representations Rafael Rivera Soto, Kailin Koch, Aleem Khan, Barry Chen, Marcus Bishop, Nicholas Andrews

A Neural Framework for Generalized Causal Sensitivity Analysis Dennis Frauen, Fergus Imrie, Alicia Curth, Valentyn Melnychuk, Stefan Feuerriegel, Mihaela van der Schaar

$\mathcal{B}$-Coder: Value-Based Deep Reinforcement Learning for Program Synthesis Zishun Yu, Yunzhe Tao, Liyu Chen, TAO SUN, Hongxia Yang

Learning Over Molecular Conformer Ensembles: Datasets and Benchmarks Yanqiao Zhu, Jeehyun Hwang, Keir Adams, Zhen Liu, Bozhao Nan, Brock Stenfors, Yuanqi Du, Jatin Chauhan, Olaf Wiest, Olexandr Isayev, Connor Coley, Yizhou Sun, Wei Wang

Augmented Bayesian Policy Search Mahdi Kallel, Debabrota Basu, Riad Akrour, Carlo D'Eramo

In defense of parameter sharing for model-compression Aditya Desai, Anshumali Shrivastava

Multimodal Web Navigation with Instruction-Finetuned Foundation Models Hiroki Furuta, Kuang-Huei Lee, Ofir Nachum, Yutaka Matsuo, Aleksandra Faust, Shixiang Gu, Izzeddin Gur

Provable Offline Preference-Based Reinforcement Learning Wenhao Zhan, Masatoshi Uehara, Nathan Kallus, Jason Lee, Wen Sun

Improved Active Learning via Dependent Leverage Score Sampling Atsushi Shimizu, Xiaoou Cheng, Christopher Musco, Jonathan Weare

What Matters to You? Towards Visual Representation Alignment for Robot Learning Thomas Tian, Chenfeng Xu, Masayoshi Tomizuka, Jitendra Malik, Andrea Bajcsy

A Lie Group Approach to Riemannian Batch Normalization Ziheng Chen, Yue Song, Yunmei Liu, Nicu Sebe

Skip-Attention: Improving Vision Transformers by Paying Less Attention Shashank Venkataramanan, Amir Ghodrati, Yuki Asano, Fatih Porikli, Amirhossein Habibian

Biased Temporal Convolution Graph Network for Time Series Forecasting with Missing Values Xiaodan Chen, Xiucheng Li, Bo Liu, Zhijun Li

On the Parameterization of Second-Order Optimization Effective towards the Infinite Width Satoki Ishikawa, Ryo Karakida

Parsing neural dynamics with infinite recurrent switching linear dynamical systems Victor Geadah, International Brain Laboratory, Jonathan Pillow

LLM-CXR: Instruction-Finetuned LLM for CXR Image Understanding and Generation Suhyeon Lee, Won Jun Kim, Jinho Chang, Jong Chul YE

Compositional Generative Inverse Design Tailin Wu, Takashi Maruyama, Long Wei, Tao Zhang, Yilun Du, Gianluca Iaccarino, Jure Leskovec

DDMI: Domain-agnostic Latent Diffusion Models for Synthesizing High-Quality Implicit Neural Representations Dogyun Park, Sihyeon Kim, Sojin Lee, Hyunwoo Kim

LightHGNN: Distilling Hypergraph Neural Networks into MLPs for 100x Faster Inference Yifan Feng, Yihe Luo, Shihui Ying, Yue Gao

Optimal Sample Complexity for Average Reward Markov Decision Processes Shengbo Wang, Jose Blanchet, Peter Glynn

Making Retrieval-Augmented Language Models Robust to Irrelevant Context Ori Yoran, Tomer Wolfson, Ori Ram, Jonathan Berant

An Investigation of Representation and Allocation Harms in Contrastive Learning Subha Maity, Mayank Agarwal, Mikhail Yurochkin, Yuekai Sun

Semantic Flow: Learning Semantic Fields of Dynamic Scenes from Monocular Videos Fengrui Tian, Yueqi Duan, Angtian Wang, Jianfei Guo, Shaoyi Du

Prometheus: Inducing Fine-Grained Evaluation Capability in Language Models Seungone Kim, Jay Shin, yejin cho, Joel Jang, Shayne Longpre, Hwaran Lee, Sangdoo Yun, Ryan S Shin, Sungdong Kim, James Thorne, Minjoon Seo

Understanding prompt engineering may not require rethinking generalization Victor Akinwande, Yiding Jiang, Dylan Sam, Zico Kolter

Entity-Centric Reinforcement Learning for Object Manipulation from Pixels Dan Haramati, Tal Daniel, Aviv Tamar

How I Warped Your Noise: a Temporally-Correlated Noise Prior for Diffusion Models Pascal Chang, Jingwei Tang, Markus Gross, Vinicius Da Costa De Azevedo

Decongestion by Representation: Learning to Improve Economic Welfare in Marketplaces Omer Nahum, Gali Noti, David Parkes, Nir Rosenfeld

Neuro-Inspired Information-Theoretic Hierarchical Perception for Multimodal Learning Xiongye Xiao, Gengshuo Liu, Gaurav Gupta, Defu Cao, Shixuan Li, Yaxing Li, Tianqing Fang, Mingxi Cheng, Paul Bogdan

On Differentially Private Federated Linear Contextual Bandits Xingyu Zhou, Sayak Ray Chowdhury

$\infty$-Diff: Infinite Resolution Diffusion with Subsampled Mollified States Sam Bond-Taylor, Chris G Willcocks

Neural Polynomial Gabor Fields for Macro Motion Analysis Chen Geng, Koven Yu, Sida Peng, Xiaowei Zhou, Jiajun Wu

Consistency Training with Learnable Data Augmentation for Graph Anomaly Detection with Limited Supervision Nan Chen, Zemin Liu, Bryan Hooi, Bingsheng He, Rizal Fathony, Jun Hu, Jia Chen

Fast Hyperboloid Decision Tree Algorithms Philippe Chlenski, Ethan Turok, Antonio Moretti, Itsik Pe'er

Matryoshka Diffusion Models Jiatao Gu, Shuangfei Zhai, Yizhe Zhang, Joshua Susskind, Navdeep Jaitly

Cascading Reinforcement Learning Yihan Du, R. Srikant, Wei Chen

Learning to Compose: Improving Object Centric Learning by Injecting Compositionality Whie Jung, Jaehoon Yoo, Sungjin Ahn, Seunghoon Hong

Overcoming the Pitfalls of Vision-Language Model Finetuning for OOD Generalization Yuhang Zang, Hanlin Goh, Joshua Susskind, Chen Huang

DreamClean: Restoring Clean Image Using Deep Diffusion Prior Jie Xiao, Ruili Feng, Han Zhang, Zhiheng Liu, Zhantao Yang, Yurui Zhu, Xueyang Fu, Kai Zhu, Yu Liu, Zheng-Jun Zha

Negatively Correlated Ensemble Reinforcement Learning for Online Diverse Game Level Generation Ziqi Wang, Chengpeng Hu, Jialin Liu, Xin Yao

LILO: Learning Interpretable Libraries by Compressing and Documenting Code Gabriel Grand, Lio Wong, Maddy Bowers, Theo X. Olausson, Muxin Liu, Joshua B Tenenbaum, Jacob Andreas

Frequency-Aware Transformer for Learned Image Compression Han Li, Shaohui Li, Wenrui Dai, Chenglin Li, Junni Zou, Hongkai Xiong

Enhancing Human-AI Collaboration Through Logic-Guided Reasoning Chengzhi Cao, Yinghao Fu, Sheng Xu, Ruimao Zhang, Shuang Li

Provably Efficient Iterated CVaR Reinforcement Learning with Function Approximation and Human Feedback Yu Chen, Yihan Du, Pihe Hu, Siwei Wang, Desheng Wu, Longbo Huang

Implicit Neural Representations and the Algebra of Complex Wavelets T Mitchell Roddenberry, Vishwanath Saragadam, Maarten V de Hoop, Richard Baraniuk

Sentence-level Prompts Benefit Composed Image Retrieval Yang Bai, Xinxing Xu, Yong Liu, Salman Khan, Fahad Khan, Wangmeng Zuo, Rick Siow Mong Mong, Chun-Mei Feng

Single Motion Diffusion Sigal Raab, Inbal Leibovitch, Guy Tevet, Moab Arar, Amit Bermano, Daniel Cohen-Or

Mitigating the Curse of Dimensionality for Certified Robustness via Dual Randomized Smoothing Song Xia, Yi Yu, Jiang Xudong, Henghui Ding

Graphical Multioutput Gaussian Process with Attention Yijue Dai, Wenzhong Yan, Feng Yin

Neural Atoms: Propagating Long-range Interaction in Molecular Graphs through Efficient Communication Channel Xuan Li, (Andrew) Zhanke Zhou, Jiangchao Yao, Yu Rong, Lu Zhang, Bo Han

OVOR: OnePrompt with Virtual Outlier Regularization for Rehearsal-Free Class-Incremental Learning Wei-Cheng Huang, Chun-Fu Chen, Hsiang Hsu

KITAB: Evaluating LLMs on Constraint Satisfaction for Information Retrieval Marah I Abdin, Suriya Gunasekar, Varun Chandrasekaran, Jerry Li, Mert Yuksekgonul, Rahee Peshawaria, Ranjita Naik, Besmira Nushi

Retro-fallback: retrosynthetic planning in an uncertain world Austin Tripp, Krzysztof Maziarz, Sarah Lewis, Marwin Segler, José Miguel Hernández Lobato

WizardLM: Empowering Large Pre-Trained Language Models to Follow Complex Instructions Can Xu, Qingfeng Sun, Kai Zheng, Xiubo Geng, Pu Zhao, Jiazhan Feng, Chongyang Tao, Qingwei Lin, Daxin Jiang

Diffusion Models for Multi-Task Generative Modeling Changyou Chen, Han Ding, Bunyamin Sisman, Yi Xu, Ouye Xie, Benjamin Yao, son tran, Belinda Zeng

Rethinking the Power of Graph Canonization in Graph Representation Learning with Stability Zehao Dong, Muhan Zhang, Philip Payne, Michael Province, Carlos Cruchaga, Tianyu Zhao, Fuhai Li, Yixin Chen

WildFusion: Learning 3D-Aware Latent Diffusion Models in View Space Katja Schwarz, Seung Wook Kim, Jun Gao, Sanja Fidler, Andreas Geiger, Karsten Kreis

Jailbreak in pieces: Compositional Adversarial Attacks on Multi-Modal Language Models Erfan Shayegani, Yue Dong, Nael Abu-Ghazaleh

STanHop: Sparse Tandem Hopfield Model for Memory-Enhanced Time Series Prediction Yu-Hsuan Wu, Jerry Yao-Chieh Hu, Weijian Li, Bo-Yu Chen, Han Liu

A Framework for Inference Inspired by Human Memory Mechanisms Xiangyu Zeng, Jie Lin, Piao Hu, Ruizheng Huang, Zhicheng Zhang

Bellman Optimal Stepsize Straightening of Flow-Matching Models Bao Nguyen, Binh Nguyen, Viet Anh Nguyen

Clifford Group Equivariant Simplicial Message Passing Networks Cong Liu, David Ruhe, Floor Eijkelboom, Patrick Forré

Fine-tuning Aligned Language Models Compromises Safety, Even When Users Do Not Intend To! Xiangyu Qi, Yi Zeng, Tinghao Xie, Pin-Yu Chen, Ruoxi Jia, Prateek Mittal, Peter Henderson

Graph Lottery Ticket Automated Guibin Zhang, Kun Wang, Wei Huang, Yanwei Yue, Yang Wang, Roger Zimmermann, Aojun Zhou, Dawei Cheng, Jin Zeng, Yuxuan Liang

Beyond Spatio-Temporal Representations: Evolving Fourier Transform for Temporal Graphs Anson Simon Bastos, Kuldeep Singh, Abhishek Nadgeri, Manish Singh, Toyotaro Suzumura

SWAP-NAS: Sample-Wise Activation Patterns for Ultra-fast NAS Yameng Peng, Andy Song, Haytham Fayek, Vic Ciesielski, Xiaojun Chang

3D Feature Prediction for Masked-AutoEncoder-Based Point Cloud Pretraining Siming Yan, Yuqi Yang, Yu-Xiao Guo, Hao Pan, Peng-Shuai Wang, 童欣 TONG XIN, Yang Liu, Qixing Huang

Video Language Planning Yilun Du, Sherry Yang, Pete Florence, Fei Xia, Ayzaan Wahid, brian ichter, Pierre Sermanet, Tianhe Yu, Pieter Abbeel, Joshua B Tenenbaum, Leslie Kaelbling, Andy Zeng, Jonathan Tompson

Sufficient conditions for offline reactivation in recurrent neural networks Nanda H Krishna, Colin Bredenberg, Daniel Levenstein, Blake A Richards, Guillaume Lajoie

Transformers as Decision Makers: Provable In-Context Reinforcement Learning via Supervised Pretraining Licong Lin, Yu Bai, Song Mei

Turning large language models into cognitive models Marcel Binz, Eric Schulz

Large Language Models to Enhance Bayesian Optimization Tennison Liu, Nicolás Astorga, Nabeel Seedat, Mihaela van der Schaar

T-Rep: Representation Learning for Time Series using Time-Embeddings Archibald Fraikin, Adrien Bennetot, Stephanie Allassonniere

A Primal-Dual Approach to Solving Variational Inequalities with General Constraints Tatjana Chavdarova, Tong Yang, Matteo Pagliardini, Michael Jordan

Towards Imitation Learning to Branch for MIP: A Hybrid Reinforcement Learning based Sample Augmentation Approach Changwen Zhang, wenli ouyang, Hao Yuan, Liming Gong, Yong Sun, Ziao Guo, Zhichen Dong, Junchi Yan

When should we prefer Decision Transformers for Offline Reinforcement Learning? Prajjwal Bhargava, Rohan Chitnis, Alborz Geramifard, Shagun Sodhani, Amy Zhang

Memory-Assisted Sub-Prototype Mining for Universal Domain Adaptation Yuxiang (YU-HSIANG) LAI, Yi Zhou, Xinghong Liu, Tao Zhou

Towards Robust Out-of-Distribution Generalization Bounds via Sharpness Yingtian Zou, Kenji Kawaguchi, Yingnan Liu, Jiashuo Liu, Mong-Li Lee, Wynne Hsu

Efficient Episodic Memory Utilization of Cooperative Multi-Agent Reinforcement Learning Hyungho Na, Yunkyeong Seo, Il-chul Moon

Continual Learning on a Diet: Learning from Sparsely Labeled Streams Under Constrained Computation Wenxuan Zhang, Youssef Mohamed, Bernard Ghanem, Philip Torr, Adel Bibi, Mohamed Elhoseiny

Replay across Experiments: A Natural Extension of Off-Policy RL Dhruva Tirumala, Thomas Lampe, Jose Enrique Chen, Tuomas Haarnoja, Sandy Huang, Guy Lever, Ben Moran, Tim Hertweck, Leonard Hasenclever, Martin Riedmiller, Nicolas Heess, Markus Wulfmeier

Generative Adversarial Equilibrium Solvers Denizalp Goktas, David Parkes, Ian Gemp, Luke Marris, Georgios Piliouras, Romuald Elie, Guy Lever, Andrea Tacchetti

LEGO-Prover: Neural Theorem Proving with Growing Libraries Haiming Wang, Huajian Xin, Chuanyang Zheng, Zhengying Liu, Qingxing Cao, Yinya Huang, Jing Xiong, Han Shi, Enze Xie, Jian Yin, Zhenguo Li, Xiaodan Liang

Towards Foundation Models for Knowledge Graph Reasoning Mikhail Galkin, Xinyu Yuan, Hesham Mostafa, Jian Tang, Zhaocheng Zhu

DragonDiffusion: Enabling Drag-style Manipulation on Diffusion Models Chong Mou, Xintao WANG, Jiechong Song, Ying Shan, Jian Zhang

Label-free Node Classification on Graphs with Large Language Models (LLMs) Zhikai Chen, Haitao Mao, Hongzhi Wen, Haoyu Han, Wei Jin, Haiyang Zhang, Hui Liu, Jiliang Tang

Imitation Learning from Observation with Automatic Discount Scheduling Yuyang Liu, Weijun Dong, Yingdong Hu, Chuan Wen, Zhao-Heng Yin, Chongjie Zhang, Yang Gao

Learning with a Mole: Transferable latent spatial representations for navigation without reconstruction Guillaume Bono, Leonid Antsfeld, Assem Sadek, Gianluca Monaci, Christian Wolf

Machine Unlearning for Image-to-Image Generative Models Guihong Li, Hsiang Hsu, Chun-Fu Chen, Radu Marculescu

ModernTCN: A Modern Pure Convolution Structure for General Time Series Analysis DongHao Luo, Xue Wang

Byzantine Robust Cooperative Multi-Agent Reinforcement Learning as a Bayesian Game Simin Li, Jun Guo, Jingqiao Xiu, Ruixiao Xu, Xin Yu, Jiakai Wang, Aishan Liu, Yaodong Yang, Xianglong Liu

SpeechTokenizer: Unified Speech Tokenizer for Speech Language Models Xin Zhang, Dong Zhang, Shimin Li, Yaqian Zhou, Xipeng Qiu

Copula Conformal prediction for multi-step time series prediction Sophia Sun, Rose Yu

Multi-Source Diffusion Models for Simultaneous Music Generation and Separation Giorgio Mariani, Irene Tallini, Emilian Postolache, Michele Mancusi, Luca Cosmo, Emanuele Rodolà

Federated Wasserstein Distance alain rakotomamonjy, Kimia Nadjahi, Liva Ralaivola

Learning to Solve Bilevel Programs with Binary Tender Bo Zhou, Ruiwei Jiang, Siqian Shen

Elastic Feature Consolidation For Cold Start Exemplar-Free Incremental Learning Simone Magistri, Tomaso Trinci, Albin Soutif--Cormerais, Joost van de Weijer, Andrew Bagdanov

YaRN: Efficient Context Window Extension of Large Language Models Bowen Peng, Jeffrey Quesnelle, Honglu Fan, Enrico Shippole

Is ImageNet worth 1 video? Learning strong image encoders from 1 long unlabelled video Shashank Venkataramanan, Mamshad Nayeem Rizve, Joao Carreira, Yuki Asano, Yannis Avrithis

Provably Robust Conformal Prediction with Improved Efficiency Ge Yan, Yaniv Romano, Tsui-Wei Weng

DistillSpec: Improving Speculative Decoding via Knowledge Distillation Yongchao Zhou, Kaifeng Lyu, Ankit Singh Rawat, Aditya Krishna Menon, Afshin Rostamizadeh, Sanjiv Kumar, Jean-François Kagy, Rishabh Agarwal

Probabilistically Rewired Message-Passing Neural Networks Chendi Qian, Andrei Manolache, Kareem Ahmed, Zhe Zeng, Guy Van den Broeck, Mathias Niepert, Christopher Morris

One Step of Gradient Descent is Provably the Optimal In-Context Learner with One Layer of Linear Self-Attention Arvind Mahankali, Tatsunori Hashimoto, Tengyu Ma

Attention Satisfies: A Constraint-Satisfaction Lens on Factual Errors of Language Models Mert Yuksekgonul, Varun Chandrasekaran, Erik Jones, Suriya Gunasekar, Ranjita Naik, Hamid Palangi, Ece Kamar, Besmira Nushi

Towards Reliable and Efficient Backdoor Trigger Inversion via Decoupling Benign Features Xiong Xu, Kunzhe Huang, Yiming Li, Zhan Qin, Kui Ren

LipVoicer: Generating Speech from Silent Videos Guided by Lip Reading Yochai Yemini, Aviv Shamsian, Lior Bracha, Sharon Gannot, Ethan Fetaya

How Realistic Is Your Synthetic Data? Constraining Deep Generative Models for Tabular Data Mihaela Stoian, Salijona Dyrmishi, Maxime Cordy, Thomas Lukasiewicz, Eleonora Giunchiglia

Mask-Based Modeling for Neural Radiance Fields Ganlin Yang, Guoqiang Wei, Zhizheng Zhang, Yan Lu, Dong Liu

Source-Free and Image-Only Unsupervised Domain Adaptation for Category Level Object Pose Estimation Prakhar Kaushik, Aayush Mishra, Adam Kortylewski, Alan Yuille

Uni-O4: Unifying Online and Offline Deep Reinforcement Learning with Multi-Step On-Policy Optimization Kun LEI, Zhengmao He, Chenhao Lu, Kaizhe Hu, Yang Gao, Huazhe Xu

Curriculum reinforcement learning for quantum architecture search under hardware errors Yash J. Patel, Akash Kundu, Mateusz Ostaszewski, Xavier Bonet-Monroig, Vedran Dunjko, Onur Danaci

CAS: A Probability-Based Approach for Universal Condition Alignment Score Chunsan Hong, ByungHee Cha, Tae-Hyun Oh

Dirichlet-based Per-Sample Weighting by Transition Matrix for Noisy Label Learning HeeSun Bae, Seungjae Shin, Byeonghu Na, Il-chul Moon

Flow to Better: Offline Preference-based Reinforcement Learning via Preferred Trajectory Generation Zhilong Zhang, Yihao Sun, Junyin Ye, Tian-Shuo Liu, Jiaji Zhang, Yang Yu

PeFLL: Personalized Federated Learning by Learning to Learn Jonathan Scott, Hossein Zakerinia, Christoph Lampert

Guaranteed Approximation Bounds for Mixed-Precision Neural Operators Renbo Tu, Colin White, Jean Kossaifi, Boris Bonev, Gennady Pekhimenko, Kamyar Azizzadenesheli, anima anandkumar

Augmenting Transformers with Recursively Composed Multi-grained Representations Xiang Hu, Qingyang Zhu, Kewei Tu, Wei Wu

Optimal transport based adversarial patch to leverage large scale attack transferability Pol Labarbarie, Adrien CHAN-HON-TONG, Stéphane Herbin, Milad Leyli-abadi

Training Unbiased Diffusion Models From Biased Dataset Yeongmin Kim, Byeonghu Na, Minsang Park, JoonHo Jang, Dongjun Kim, Wanmo Kang, Il-chul Moon

Let 2D Diffusion Model Know 3D-Consistency for Robust Text-to-3D Generation Junyoung Seo, Wooseok Jang, Min-Seop Kwak, Inès Hyeonsu Kim, Jaehoon Ko, Junho Kim, Jin-Hwa Kim, Jiyoung Lee, Seungryong Kim

GPAvatar: Generalizable and Precise Head Avatar from Image(s) Xuangeng Chu, Yu Li, Ailing Zeng, Tianyu Yang, Lijian Lin, Yunfei Liu, Tatsuya Harada

MINT: Evaluating LLMs in Multi-turn Interaction with Tools and Language Feedback Xingyao Wang, Zihan Wang, Jiateng Liu, Yangyi Chen, Lifan Yuan, Hao Peng, Heng Ji

RAPTOR: Recursive Abstractive Processing for Tree-Organized Retrieval Parth Sarthi, Salman Abdullah, Aditi Tuli, Shubh Khanna, Anna Goldie, Christopher Manning

ECoFLaP: Efficient Coarse-to-Fine Layer-Wise Pruning for Vision-Language Models Yi-Lin Sung, Jaehong Yoon, Mohit Bansal

Mitigating Emergent Robustness Degradation while Scaling Graph Learning Xiangchi Yuan, Chunhui Zhang, Yijun Tian, Yanfang Ye, Chuxu Zhang

MiniLLM: Knowledge Distillation of Large Language Models Yuxian Gu, Li Dong, Furu Wei, Minlie Huang

Robust Angular Synchronization via Directed Graph Neural Networks Yixuan He, Gesine Reinert, David Wipf, Mihai Cucuringu

Variational Inference for SDEs Driven by Fractional Noise Rembert Daems, Manfred Opper, Guillaume Crevecoeur, Tolga Birdal

On Error Propagation of Diffusion Models Yangming Li, Mihaela van der Schaar

Large Language Models Cannot Self-Correct Reasoning Yet Jie Huang, Xinyun Chen, Swaroop Mishra, Huaixiu Steven Zheng, Adams Yu, Xinying Song, Denny Zhou

Post-hoc bias scoring is optimal for fair classification Wenlong Chen, Yegor Klochkov, Yang Liu

GenCorres: Consistent Shape Matching via Coupled Implicit-Explicit Shape Generative Models Haitao Yang, Xiangru Huang, Bo Sun, Chandrajit Bajaj, Qixing Huang

Towards Identifiable Unsupervised Domain Translation: A Diversified Distribution Matching Approach Sagar Shrestha, Xiao Fu

Image Translation as Diffusion Visual Programmers Cheng Han, James Liang, Qifan Wang, MAJID RABBANI, Sohail Dianat, Raghuveer Rao, Yingnian Wu, Dongfang Liu

Grokking in Linear Estimators -- A Solvable Model that Groks without Understanding Noam Levi, Alon Beck, Yohai Bar-Sinai

Neural Rate Control for Learned Video Compression yiwei zhang, Guo Lu, Yunuo Chen, Shen Wang, Yibo Shi, Jing Wang, Li Song

Ensemble Distillation for Unsupervised Constituency Parsing Behzad Shayegh, Yanshuai Cao, Xiaodan Zhu, Jackie Cheung, Lili Mou

Dynamic Sparse Training with Structured Sparsity Mike Lasby, Anna Golubeva, Utku Evci, Mihai Nica, Yani Ioannou

Navigating Dataset Documentations in AI: A Large-Scale Analysis of Dataset Cards on HuggingFace Xinyu Yang, Victor Weixin Liang, James Y Zou

The Trickle-down Impact of Reward Inconsistency on RLHF Lingfeng Shen, Sihao Chen, Linfeng Song, Lifeng Jin, Baolin Peng, Haitao Mi, Daniel Khashabi, Dong Yu

Privacy-Preserving In-Context Learning with Differentially Private Few-Shot Generation Xinyu Tang, Richard Shin, Huseyin Inan, Andre Manoel, Niloofar Mireshghallah, Zinan Lin, Sivakanth Gopi, Janardhan Kulkarni, Robert Sim

Fine-tuning Multimodal LLMs to Follow Zero-shot Demonstrative Instructions Juncheng Li, Kaihang Pan, Zhiqi Ge, Minghe Gao, Wei Ji, Wenqiao Zhang, Tat-Seng Chua, Siliang Tang, Hanwang Zhang, Yueting Zhuang

Dropout-Based Rashomon Set Exploration for Efficient Predictive Multiplicity Estimation Hsiang Hsu, Guihong Li, Shaohan Hu, Chun-Fu Chen

Exploring the Common Appearance-Boundary Adaptation for Nighttime Optical Flow Hanyu Zhou, Yi Chang, Haoyue Liu, YAN WENDING, Yuxing Duan, Zhiwei Shi, Luxin Yan

Assessing Uncertainty in Similarity Scoring: Performance & Fairness in Face Recognition Jean-Rémy Conti, Stephan CLEMENCON

DMV3D: Denoising Multi-view Diffusion Using 3D Large Reconstruction Model Yinghao Xu, Hao Tan, Fujun Luan, Sai Bi, Peng Wang, Jiahao Li, Zifan Shi, Kalyan Sunkavalli, Gordon Wetzstein, Zexiang Xu, Kai Zhang

RECOMBINER: Robust and Enhanced Compression with Bayesian Implicit Neural Representations Jiajun He, Gergely Flamich, Zongyu Guo, José Miguel Hernández Lobato

Querying Easily Flip-flopped Samples for Deep Active Learning Seong Jin Cho, Gwangsu Kim, Junghyun Lee, Jinwoo Shin, Chang Yoo

Bootstrapping Variational Information Pursuit with Large Language and Vision Models for Interpretable Image Classification Aditya Chattopadhyay, Kwan Ho Ryan Chan, Rene Vidal

Robustifying State-space Models for Long Sequences via Approximate Diagonalization Annan Yu, Arnur Nigmetov, Dmitriy Morozov, Michael W Mahoney, N. Benjamin Erichson

Error Feedback Reloaded: From Quadratic to Arithmetic Mean of Smoothness Constants Peter Richtarik, Elnur Gasanov, Konstantin Burlachenko

PerceptionCLIP: Visual Classification by Inferring and Conditioning on Contexts Bang An, Sicheng Zhu, Michael-Andrei Panaitescu-Liess, Chaithanya Kumar Mummadi, Furong Huang

Addressing Loss of Plasticity and Catastrophic Forgetting in Continual Learning Mohamed Elsayed, A. Rupam Mahmood

Zero-Shot Robotic Manipulation with Pre-Trained Image-Editing Diffusion Models Kevin Black, Mitsuhiko Nakamoto, Pranav Atreya, Homer Walke, Chelsea Finn, Aviral Kumar, Sergey Levine

Adaptive Regularization of Representation Rank as an Implicit Constraint of Bellman Equation Qiang HE, Tianyi Zhou, Meng Fang, Setareh Maghsudi

G$^2$N$^2$ : Weisfeiler and Lehman go grammatical Jason Piquenot, Aldo Moscatelli, Maxime Berar, Pierre Héroux, Romain Raveaux, Jean-Yves RAMEL, Sébastien Adam

How Does Unlabeled Data Provably Help Out-of-Distribution Detection? Xuefeng Du, Zhen Fang, Ilias Diakonikolas, Yixuan Li

SEPT: Towards Efficient Scene Representation Learning for Motion Prediction Zhiqian Lan, Yuxuan Jiang, Yao Mu, Chen Chen, Shengbo Li

DiffAR: Denoising Diffusion Autoregressive Model for Raw Speech Waveform Generation Roi Benita, Michael Elad, Joseph Keshet

Causal-StoNet: Causal Inference for High-Dimensional Complex Data Yaxin Fang, Faming Liang

Solving Diffusion ODEs with Optimal Boundary Conditions for Better Image Super-Resolution Yiyang Ma, Huan Yang, Wenhan Yang, Jianlong Fu, Jiaying Liu

Large Language Models as Generalizable Policies for Embodied Tasks Andrew Szot, Max Schwarzer, Harsh Agrawal, Bogdan Mazoure, Katherine Metcalf, Walter Talbott, Natalie Mackraz, R Devon Hjelm, Alexander Toshev

Enhancing Instance-Level Image Classification with Set-Level Labels Renyu Zhang, Aly Khan, Yuxin Chen, Robert Grossman

Learning to Relax: Setting Solver Parameters Across a Sequence of Linear System Instances Mikhail Khodak, Edmond Chow, Nina Balcan, Ameet Talwalkar

Compositional Preference Models for Aligning LMs DONGYOUNG GO, Tomek Korbak, Germàn Kruszewski, Jos Rozen, Marc Dymetman

Advancing the Lower Bounds: an Accelerated, Stochastic, Second-order Method with Optimal Adaptation to Inexactness Artem Agafonov, Dmitry Kamzolov, Alexander Gasnikov, Ali Kavis, Kimon Antonakopoulos, Volkan Cevher, Martin Takáč

GNeRP: Gaussian-guided Neural Reconstruction of Reflective Objects with Noisy Polarization Priors LI Yang, RUIZHENG WU, Jiyong Li, YINGCONG CHEN

BarLeRIa: An Efficient Tuning Framework for Referring Image Segmentation Yaoming Wang, Li Jin, XIAOPENG ZHANG, Bowen Shi, Chenglin Li, Wenrui Dai, Hongkai Xiong, Qi Tian

Generalized Neural Sorting Networks with Error-Free Differentiable Swap Functions Jungtaek Kim, Jeongbeen Yoon, Minsu Cho

Beyond Memorization: Violating Privacy via Inference with Large Language Models Robin Staab, Mark Vero, Mislav Balunovic, Martin Vechev

DreamGaussian: Generative Gaussian Splatting for Efficient 3D Content Creation Jiaxiang Tang, Jiawei Ren, Hang Zhou, Ziwei Liu, Gang Zeng

Dichotomy of Early and Late Phase Implicit Biases Can Provably Induce Grokking Kaifeng Lyu, Jikai Jin, Zhiyuan Li, Simon Du, Jason Lee, Wei Hu

TEDDY: Trimming Edges with Degree-based Discrimination Strategy Hyunjin Seo, Jihun Yun, Eunho Yang

Exploring Target Representations for Masked Autoencoders xingbin liu, Jinghao Zhou, Tao Kong, Xianming Lin, Rongrong Ji

Symphony: Symmetry-Equivariant Point-Centered Spherical Harmonics for 3D Molecule Generation Ameya Daigavane, Song Eun Kim, Mario Geiger, Tess Smidt

T-MARS: Improving Visual Representations by Circumventing Text Feature Learning Pratyush Maini, Sachin Goyal, Zachary Lipton, Zico Kolter, Aditi Raghunathan

Label-Noise Robust Diffusion Models Byeonghu Na, Yeongmin Kim, HeeSun Bae, Jung Hyun Lee, Se Jung Kwon, Wanmo Kang, Il-chul Moon

The Need for Speed: Pruning Transformers with One Recipe Samir Khaki, Konstantinos Plataniotis

Synergistic Patch Pruning for Vision Transformer: Unifying Intra- & Inter-Layer Patch Importance Yuyao Zhang, Lan Wei, Nikolaos Freris

Concept Bottleneck Generative Models Aya Abdelsalam Ismail, Julius Adebayo, Hector Corrada Bravo, Stephen Ra, Kyunghyun Cho

Connecting Large Language Models with Evolutionary Algorithms Yields Powerful Prompt Optimizers Qingyan Guo, Rui Wang, Junliang Guo, Bei Li, Kaitao Song, Xu Tan, Guoqing Liu, Jiang Bian, Yujiu Yang

VFLAIR: A Research Library and Benchmark for Vertical Federated Learning TIANYUAN ZOU, Zixuan GU, Yu He, Hideaki Takahashi, Yang Liu, Ya-Qin Zhang

Safety-Tuned LLaMAs: Lessons From Improving the Safety of Large Language Models that Follow Instructions Federico Bianchi, Mirac Suzgun, Giuseppe Attanasio, Paul Röttger, Dan Jurafsky, Tatsunori Hashimoto, James Y Zou

Noisy Interpolation Learning with Shallow Univariate ReLU Networks Nirmit Joshi, Gal Vardi, Nathan Srebro

Leveraging Unpaired Data for Vision-Language Generative Models via Cycle Consistency Tianhong Li, Sangnie Bhardwaj, Yonglong Tian, Han Zhang, Jarred Barber, Dina Katabi, Guillaume Lajoie, Huiwen Chang, Dilip Krishnan

Beating Price of Anarchy and Gradient Descent without Regret in Potential Games Iosif Sakos, Stefanos Leonardos, Stelios Stavroulakis, William Overman, Ioannis Panageas, Georgios Piliouras

PROGRAM: PROtotype GRAph Model based Pseudo-Label Learning for Test-Time Adaptation Haopeng Sun, Lumin Xu, Sheng Jin, Ping Luo, Chen Qian, Wentao Liu

Partitioning Message Passing for Graph Fraud Detection Wei Zhuo, Zemin Liu, Bryan Hooi, Bingsheng He, Guang Tan, Rizal Fathony, Jia Chen

Headless Language Models: Learning without Predicting with Contrastive Weight Tying Nathan Godey, Éric Clergerie, Benoît Sagot

Towards the Fundamental Limits of Knowledge Transfer over Finite Domains Qingyue Zhao, Banghua Zhu

Zero-Shot Robustification of Zero-Shot Models Dyah Adila, Changho Shin, Linrong Cai, Frederic Sala

GOAt: Explaining Graph Neural Networks via Graph Output Attribution Shengyao Lu, Keith G Mills, Jiao He, Bang Liu, Di Niu

A Linear Algebraic Framework for Counterfactual Generation Jong-Hoon Ahn, Akshay Vashist

Unprocessing Seven Years of Algorithmic Fairness André F. Cruz, Moritz Hardt

DiLu: A Knowledge-Driven Approach to Autonomous Driving with Large Language Models Licheng Wen, DAOCHENG FU, Xin Li, Xinyu Cai, Tao MA, Pinlong Cai, Min Dou, Botian Shi, Liang He, Yu Qiao

AutoCast++: Enhancing World Event Prediction with Zero-shot Ranking-based Context Retrieval Qi Yan, Raihan Seraj, Jiawei He, Lili Meng, Tristan Sylvain

Leveraging Generative Models for Unsupervised Alignment of Neural Time Series Data Ayesha Vermani, Il Memming Park, Josue Nassar

KW-Design: Pushing the Limit of Protein Design via Knowledge Refinement Zhangyang Gao, Cheng Tan, Xingran Chen, Yijie Zhang, Jun Xia, Siyuan Li, Stan Z Li

TapMo: Shape-aware Motion Generation of Skeleton-free Characters Jiaxu Zhang, Shaoli Huang, Zhigang Tu, Xin Chen, Xiaohang Zhan, Gang Yu, Ying Shan

WildChat: 1M ChatGPT Interaction Logs in the Wild Wenting Zhao, Xiang Ren, Jack Hessel, Claire Cardie, Yejin Choi, Yuntian Deng

On the Hardness of Online Nonconvex Optimization with Single Oracle Feedback Ziwei Guan, Yi Zhou, Yingbin Liang

AnimateDiff: Animate Your Personalized Text-to-Image Diffusion Models without Specific Tuning Yuwei GUO, Ceyuan Yang, Anyi Rao, Zhengyang Liang, Yaohui Wang, Yu Qiao, Maneesh Agrawala, Dahua Lin, Bo DAI

Quadratic models for understanding catapult dynamics of neural networks Libin Zhu, Chaoyue Liu, Adityanarayanan Radhakrishnan, Misha Belkin

Can LLM-Generated Misinformation Be Detected? Canyu Chen, Kai Shu

Diffeomorphic Mesh Deformation via Efficient Optimal Transport for Cortical Surface Reconstruction Thanh-Tung Le, Khai Nguyen, shanlin sun, Kun Han, Nhat Ho, Xiaohui Xie

Probabilistic Self-supervised Representation Learning via Scoring Rules Minimization Amirhossein Vahidi, Simon Schosser, Lisa Wimmer, Yawei Li, Bernd Bischl, Eyke Hüllermeier, Mina Rezaei

AlpaGasus: Training a Better Alpaca with Fewer Data Lichang Chen, Shiyang Li, Jun Yan, Hai Wang, Kalpa Gunaratna, Vikas Yadav, Zheng Tang, Vijay Srinivasan, Tianyi Zhou, Heng Huang, Hongxia Jin

Kalman Filter for Online Classification of Non-Stationary Data Michalis Titsias, Alexandre Galashov, Amal Rannen-Triki, Razvan Pascanu, Yee Whye Teh, Jorg Bornschein

Multi-View Causal Representation Learning with Partial Observability Dingling Yao, Danru Xu, Sébastien Lachapelle, Sara Magliacane, Perouz Taslakian, Georg Martius, Julius von Kügelgen, Francesco Locatello

Multiscale Positive-Unlabeled Detection of AI-Generated Texts Yuchuan Tian, Hanting Chen, Xutao Wang, Zheyuan Bai, QINGHUA ZHANG, Ruifeng Li, Chao Xu, Yunhe Wang

Identifiable Latent Polynomial Causal Models through the Lens of Change Yuhang Liu, Zhen Zhang, Dong Gong, Mingming Gong, Biwei Huang, Anton Hengel, Kun Zhang, Javen Qinfeng Shi

LLCP: Learning Latent Causal Processes for Reasoning-based Video Question Answer Guangyi Chen, Yuke Li, Xiao Liu, Zijian Li, Eman Al Suradi, Donglai Wei, Kun Zhang

$\texttt{NAISR}$: A 3D Neural Additive Model for Interpretable Shape Representation Yining Jiao, Carlton ZDANSKI, Julia Kimbell, Andrew Prince, Cameron Worden, Samuel Kirse, Christopher Rutter, Benjamin Shields, William Dunn, Jisan Mahmud, Marc Niethammer

Topological data analysis on noisy quantum computers Ismail Akhalwaya, Shashanka Ubaru, Kenneth Clarkson, Mark Squillante, Vishnu Jejjala, Yang-Hui He, Kugendran Naidoo, Vasileios Kalantzis, Lior Horesh

Estimating Conditional Mutual Information for Dynamic Feature Selection Soham Gadgil, Ian Covert, Su-In Lee

Controlled Text Generation via Language Model Arithmetic Jasper Dekoninck, Marc Fischer, Luca Beurer-Kellner, Martin Vechev

Retrieval-Guided Reinforcement Learning for Boolean Circuit Minimization Animesh Basak Chowdhury, Marco Romanelli, Benjamin Tan, Ramesh Karri, Siddharth Garg

Can We Evaluate Domain Adaptation Models Without Target-Domain Labels? JIANFEI YANG, Hanjie Qian, Yuecong Xu, Kai Wang, Lihua Xie

DEEP NEURAL NETWORK INITIALIZATION WITH SPARSITY INDUCING ACTIVATIONS Ilan Price, Nicholas Daultry Ball, Adam Jones, Samuel Chun Hei Lam, Jared Tanner

Differentially Private Synthetic Data via Foundation Model APIs 1: Images Zinan Lin, Sivakanth Gopi, Janardhan Kulkarni, Harsha Nori, Sergey Yekhanin

Scalable Monotonic Neural Networks Hyunho Kim, Jong-Seok Lee

Are Transformers with One Layer Self-Attention Using Low-Rank Weight Matrices Universal Approximators? Tokio Kajitsuka, Issei Sato

Making LLaMA SEE and Draw with SEED Tokenizer Yuying Ge, Sijie Zhao, Ziyun Zeng, Yixiao Ge, Chen Li, Xintao WANG, Ying Shan

CNN Kernels Can Be the Best Shapelets Eric Qu, Yansen Wang, Xufang Luo, Wenqiang He, Kan Ren, Dongsheng Li

Multi-task Learning with 3D-Aware Regularization Wei-Hong Li, Steven McDonagh, Ales Leonardis, Hakan Bilen

Real-Fake: Effective Training Data Synthesis Through Distribution Matching Jianhao Yuan, Jie Zhang, Shuyang Sun, Philip Torr, Bo ZHAO

Diffusion in Diffusion: Cyclic One-Way Diffusion for Text-Vision-Conditioned Generation Ruoyu Wang, Yongqi Yang, Zhihao Qian, Ye Zhu, Yu Wu

Compressed Context Memory for Online Language Model Interaction Jang-Hyun Kim, Junyoung Yeom, Sangdoo Yun, Hyun Oh Song

Weakly Supervised Virus Capsid Detection with Image-Level Annotations in Electron Microscopy Images Hannah Kniesel, Leon Sick, Tristan Payer, Tim Bergner, Kavitha Shaga Devan, Clarissa Read, Paul Walther, Timo Ropinski, Pedro Hermosilla

PhyloGFN: Phylogenetic inference with generative flow networks MING YANG ZHOU, Zichao Yan, Elliot Layne, Nikolay Malkin, Dinghuai Zhang, Moksh Jain, Mathieu Blanchette, Yoshua Bengio

Lion Secretly Solves a Constrained Optimization: As Lyapunov Predicts Lizhang Chen, Bo Liu, Kaizhao Liang, Qiang Liu

Idempotent Generative Network Assaf Shocher, Amil Dravid, Yossi Gandelsman, Inbar Mosseri, Michael Rubinstein, Alexei Efros

Improved Analysis of Sparse Linear Regression in Local Differential Privacy Model Liyang Zhu, Meng Ding, Vaneet Aggarwal, Jinhui Xu, Di Wang

Spatially-Aware Transformers for Embodied Agents Junmo Cho, Jaesik Yoon, Sungjin Ahn

AUGCAL: Improving Sim2Real Adaptation by Uncertainty Calibration on Augmented Synthetic Images Prithvijit Chattopadhyay, Bharat Goyal, Boglarka Ecsedi, Viraj Prabhu, Judy Hoffman

FlashAttention-2: Faster Attention with Better Parallelism and Work Partitioning Tri Dao

R-EDL: Relaxing Nonessential Settings of Evidential Deep Learning Mengyuan Chen, Junyu Gao, Changsheng Xu

INViTE: INterpret and Control Vision-Language Models with Text Explanations Haozhe Chen, Junfeng Yang, Carl Vondrick, Chengzhi Mao

Predictive, scalable and interpretable knowledge tracing on structured domains Hanqi Zhou, Robert Bamler, Charley Wu, Álvaro Tejero-Cantero

Adaptive Chameleon or Stubborn Sloth: Revealing the Behavior of Large Language Models in Knowledge Conflicts Jian Xie, Kai Zhang, Jiangjie Chen, Renze Lou, Yu Su

Detecting, Explaining, and Mitigating Memorization in Diffusion Models Yuxin Wen, Yuchen Liu, Chen Chen, Lingjuan Lyu

Text2Reward: Reward Shaping with Language Models for Reinforcement Learning Tianbao Xie, Siheng Zhao, Chen Wu, Yitao Liu, Qian Luo, Victor Zhong, Yanchao Yang, Tao Yu

Optimal Sample Complexity of Contrastive Learning Noga Alon, Dmitrii Avdiukhin, Dor Elboim, Orr Fischer, Grigory Yaroslavtsev

Offline Data Enhanced On-Policy Policy Gradient with Provable Guarantees Yifei Zhou, Ayush Sekhari, Yuda Song, Wen Sun

Scaling Convex Neural Networks with Burer-Monteiro Factorization Arda Sahiner, Tolga Ergen, Batu Ozturkler, John M Pauly, Morteza Mardani, Mert Pilanci

Can Transformers Capture Spatial Relations between Objects? Chuan Wen, Dinesh Jayaraman, Yang Gao

CCIL: Continuity-Based Data Augmentation for Corrective Imitation Learning Liyiming Ke, Yunchu Zhang, Abhay Deshpande, Siddhartha Srinivasa, Abhishek Gupta

Unified Projection-Free Algorithms for Adversarial DR-Submodular Optimization Mohammad Pedramfar, Yididiya Nadew, Chris Quinn, Vaneet Aggarwal

Language Model Inversion John X. Morris, Wenting Zhao, Justin Chiu, Vitaly Shmatikov, Alexander Rush

Proximal Policy Gradient Arborescence for Quality Diversity Reinforcement Learning Sumeet Batra, Bryon Tjanaka, Matthew Fontaine, Aleksei Petrenko, Stefanos Nikolaidis, Gaurav Sukhatme

Two-timescale Extragradient for Finding Local Minimax Points Jiseok Chae, Kyuwon Kim, Donghwan Kim

Learning Grounded Action Abstractions from Language Lio Wong, Jiayuan Mao, Pratyusha Sharma, Zachary Siegel, Jiahai Feng, Noa Korneev, Joshua B Tenenbaum, Jacob Andreas

More is Better: when Infinite Overparameterization is Optimal and Overfitting is Obligatory James Simon, Dhruva Karkada, Nikhil Ghosh, Misha Belkin

Scaling physics-informed hard constraints with mixture-of-experts Nithin Chalapathi, Yiheng Du, Aditi Krishnapriyan

$\pi$2vec: Policy Representation with Successor Features Gianluca Scarpellini, Ksenia Konyushkova, Claudio Fantacci, Thomas Paine, Yutian Chen, Misha Denil

Learning from Sparse Offline Datasets via Conservative Density Estimation Zhepeng Cen, Zuxin Liu, Zitong Wang, Yihang Yao, Henry Lam, DING ZHAO

Provable Memory Efficient Self-Play Algorithm for Model-free Reinforcement Learning Na Li, Yuchen Jiao, Hangguan Shan, Shefeng Yan

Synaptic Weight Distributions Depend on the Geometry of Plasticity Roman Pogodin, Jonathan Cornford, Arna Ghosh, Gauthier Gidel, Guillaume Lajoie, Blake A Richards

Adaptive Self-training Framework for Fine-grained Scene Graph Generation Kibum Kim, Kanghoon Yoon, Yeonjun In, Jinyoung Moon, Donghyun Kim, Chanyoung Park

Efficient Heterogeneous Meta-Learning via Channel Shuffling Modulation Minh Hoang, Carl Kingsford

CAMIL: Context-Aware Multiple Instance Learning for Cancer Detection and Subtyping in Whole Slide Images olga fourkioti, Matt De Vries, Chris Bakal

Data Filtering Networks Alex Fang, Albin Madappally Jose, Amit Jain, Ludwig Schmidt, Alexander Toshev, Vaishaal Shankar

VertiBench: Advancing Feature Distribution Diversity in Vertical Federated Learning Benchmarks Zhaomin Wu, Junyi Hou, Bingsheng He

At Which Training Stage Does Code Data Help LLMs Reasoning? ma yingwei, Yue Liu, Yue Yu, Yuanliang Zhang, Yu Jiang, Changjian Wang, Shanshan Li

Equivariant Scalar Fields for Molecular Docking with Fast Fourier Transforms Bowen Jing, Tommi Jaakkola, Bonnie Berger

RLIF: Interactive Imitation Learning as Reinforcement Learning Jianlan Luo, Perry Dong, Yuexiang Zhai, Yi Ma, Sergey Levine

Views Can Be Deceiving: Improved SSL Through Feature Space Augmentation Kimia Hamidieh, Haoran Zhang, Swami Sankaranarayanan, Marzyeh Ghassemi

JoMA: Demystifying Multilayer Transformers via Joint Dynamics of MLP and Attention Yuandong Tian, Yiping Wang, Zhenyu Zhang, Beidi Chen, Simon Du

How do Language Models Bind Entities in Context? Jiahai Feng, Jacob Steinhardt

Future Language Modeling from Temporal Document History Changmao Li, Jeffrey Flanigan

AmortizedPeriod: Attention-based Amortized Inference for Periodicity Identification Hang Yu, Cong Liao, Ruolan Liu, Jianguo Li, Hu Yun, Xinzhe Wang

#InsTag: Instruction Tagging for Analyzing Supervised Fine-tuning of Large Language Models Keming Lu, Hongyi Yuan, Zheng Yuan, Runji Lin, Junyang Lin, Chuanqi Tan, Chang Zhou, Jingren Zhou

Image Inpainting via Iteratively Decoupled Probabilistic Modeling Wenbo Li, Xin Yu, Kun Zhou, Yibing Song, Zhe Lin

Rethinking and Extending the Probabilistic Inference Capacity of GNNs Tuo Xu, Lei Zou

Is Self-Repair a Silver Bullet for Code Generation? Theo X. Olausson, Jeevana Priya Inala, Chenglong Wang, Jianfeng Gao, Armando Solar-Lezama

f-FERM: A Scalable Framework for Robust Fair Empirical Risk Minimization Sina Baharlouei, Shivam Patel, Meisam Razaviyayn

On the Fairness ROAD: Robust Optimization for Adversarial Debiasing Vincent Grari, Thibault Laugel, Tatsunori Hashimoto, sylvain lamprier, Marcin Detyniecki

Gradual Optimization Learning for Conformational Energy Minimization Artem Tsypin, Leonid A. Ugadiarov, Kuzma Khrabrov, Alexander Telepov, Egor Rumiantsev, Alexey Skrynnik, Aleksandr Panov, Dmitry P. Vetrov, Elena Tutubalina, Artur Kadurin

Strategic Preys Make Acute Predators: Enhancing Camouflaged Object Detectors by Generating Camouflaged Objects Chunming He, Kai Li, Yachao Zhang, Yulun Zhang, Chenyu You, zhenhua guo, Xiu Li, Martin Danelljan, Fisher Yu

Combinatorial Bandits for Maximum Value Reward Function under Value-Index Feedback Yiliu Wang, Wei Chen, Milan Vojnovic

NeRM: Learning Neural Representations for High-Framerate Human Motion Synthesis Dong Wei, Huaijiang Sun, Bin Li, Xiaoning Sun, Shengxiang Hu, Weiqing Li, Jianfeng Lu

Reconciling Spatial and Temporal Abstractions for Goal Representation Mehdi Zadem, Sergio Mover, Sao Mai Nguyen

Variance-aware Regret Bounds for Stochastic Contextual Dueling Bandits Qiwei Di, Tao Jin, Yue Wu, Heyang Zhao, Farzad Farnoud, Quanquan Gu

L2MAC: Large Language Model Automatic Computer for Extensive Code Generation Samuel Holt, Max Ruiz Luyten, Mihaela van der Schaar

Understanding and Mitigating the Label Noise in Pre-training on Downstream Tasks Hao Chen, Jindong Wang, Ankit Parag Shah, Ran Tao, Hongxin Wei, Xing Xie, Masashi Sugiyama, Bhiksha Raj

Prototypical Information Bottlenecking and Disentangling for Multimodal Cancer Survival Prediction Yilan Zhang, Yingxue XU, Jianqi Chen, Fengying Xie, Hao CHEN

Visual Data-Type Understanding does not emerge from scaling Vision-Language Models Vishaal Udandarao, Max F. Burg, Samuel Albanie, Matthias Bethge

Nearly $d$-Linear Convergence Bounds for Diffusion Models via Stochastic Localization Joe Benton, Valentin De Bortoli, Arnaud Doucet, George Deligiannidis

Skill Machines: Temporal Logic Skill Composition in Reinforcement Learning Geraud Nangue Tasse, Devon Jarvis, Steven James, Benjamin Rosman

Learning dynamic representations of the functional connectome in neurobiological networks Luciano Dyballa, Samuel Lang, Alexandra Haslund-Gourley, Eviatar Yemini, Steven Zucker

Compressing LLMs: The Truth is Rarely Pure and Never Simple AJAY JAISWAL, Zhe Gan, Xianzhi Du, Bowen Zhang, Zhangyang Wang, Yinfei Yang

Deep Geodesic Canonical Correlation Analysis for Covariance-Based Neuroimaging Data Ce Ju, Reinmar Kobler, Liyao Tang, Cuntai Guan, Motoaki Kawanabe

ARM: Refining Multivariate Forecasting with Adaptive Temporal-Contextual Learning Jiecheng Lu, Xu Han, Shihao Yang

DyST: Towards Dynamic Neural Scene Representations on Real-World Videos Maximilian Seitzer, Sjoerd van Steenkiste, Thomas Kipf, Klaus Greff, Mehdi S. M. Sajjadi

Revisiting Deep Audio-Text Retrieval Through the Lens of Transportation Tien Manh Luong, Khai Nguyen, Nhat Ho, Reza Haffari, Dinh Phung, Lizhen Qu

CoRe-GD: A Hierarchical Framework for Scalable Graph Visualization with GNNs Florian Grötschla, Joël Mathys, Róbert Veres, Roger Wattenhofer

The Lipschitz-Variance-Margin Tradeoff for Enhanced Randomized Smoothing Blaise Delattre, Alexandre Araujo, Quentin Barthélemy, Alexandre Allauzen

Perceptual Scales Predicted by Fisher Information Metrics Jonathan Vacher, Pascal Mamassian

Online GNN Evaluation Under Test-time Graph Distribution Shifts Xin Zheng, Dongjin Song, Qingsong Wen, Bo Du, Shirui Pan

Towards domain-invariant Self-Supervised Learning with Batch Styles Standardization Marin Scalbert, Maria Vakalopoulou, Florent Couzinie-Devy

Toward Student-oriented Teacher Network Training for Knowledge Distillation Chengyu Dong, Liyuan Liu, Jingbo Shang

A Policy Gradient Method for Confounded POMDPs Mao Hong, Zhengling Qi, Yanxun Xu

Towards Offline Opponent Modeling with In-context Learning Yuheng Jing, Kai Li, Bingyun Liu, Yifan Zang, Haobo Fu, QIANG FU, Junliang Xing, Jian Cheng

Compressing Latent Space via Least Volume Qiuyi Chen, Mark Fuge

In-Context Pretraining: Language Modeling Beyond Document Boundaries Weijia Shi, Sewon Min, Maria Lomeli, Chunting Zhou, Margaret Li, Victoria Lin, Noah Smith, Luke Zettlemoyer, Scott Yih, Mike Lewis

Independent-Set Design of Experiments for Estimating Treatment and Spillover Effects under Network Interference Chencheng Cai, Xu Zhang, Edoardo Airoldi

AutoLoRa: An Automated Robust Fine-Tuning Framework Xilie Xu, Jingfeng Zhang, Mohan Kankanhalli

MogaNet: Multi-order Gated Aggregation Network Siyuan Li, Zedong Wang, Zicheng Liu, Cheng Tan, Haitao Lin, Di Wu, Zhiyuan Chen, Jiangbin Zheng, Stan Z Li

On the Limitations of Temperature Scaling for Distributions with Overlaps Muthu Chidambaram, Rong Ge

SAFLEX: Self-Adaptive Augmentation via Feature Label Extrapolation Mucong Ding, Bang An, Yuancheng Xu, Anirudh Satheesh, Furong Huang

Provably Efficient CVaR RL in Low-rank MDPs Yulai Zhao, Wenhao Zhan, Xiaoyan Hu, Ho-fung Leung, Farzan Farnia, Wen Sun, Jason Lee

Demystifying Linear MDPs and Novel Dynamics Aggregation Framework Joongkyu Lee, Min-hwan Oh

On Double Descent in Reinforcement Learning with LSTD and Random Features David Brellmann, Eloïse Berthier, David Filliat, Goran Frehse

An Agnostic View on the Cost of Overfitting in (Kernel) Ridge Regression Lijia Zhou, James Simon, Gal Vardi, Nathan Srebro

Communication-Efficient Federated Non-Linear Bandit Optimization Chuanhao Li, Chong Liu, Yu-Xiang Wang

Nougat: Neural Optical Understanding for Academic Documents Lukas Blecher, Guillem Cucurull Preixens, Thomas Scialom, Robert Stojnic

ScaleCrafter: Tuning-free Higher-Resolution Visual Generation with Diffusion Models Yingqing He, Shaoshu Yang, Haoxin Chen, Xiaodong Cun, Menghan Xia, Yong Zhang, Xintao WANG, Ran He, Qifeng Chen, Ying Shan

Measuring Vision-Language STEM Skills of Neural Models Jianhao Shen, Ye Yuan, Srbuhi Mirzoyan, Ming Zhang, Chenguang Wang

InfoCon: Concept Discovery with Generative and Discriminative Informativeness Ruizhe Liu, Qian Luo, Yanchao Yang

Towards Establishing Guaranteed Error for Learned Database Operations Sepanta Zeighami, Cyrus Shahabi

Long-Short-Range Message-Passing: A Physics-Informed Framework to Capture Non-Local Interaction for Scalable Molecular Dynamics Simulation Yunyang Li, Yusong Wang, Lin Huang, Han Yang, Xinran Wei, Jia Zhang, Tong Wang, Zun Wang, Bin Shao, Tie-Yan Liu

Posterior Sampling Based on Gradient Flows of the MMD with Negative Distance Kernel Paul Hagemann, Johannes Hertrich, Fabian Altekrüger, Robert Beinert, Jannis Chemseddine, Gabriele Steidl

TEST: Text Prototype Aligned Embedding to Activate LLM's Ability for Time Series Chenxi Sun, Hongyan Li, Yaliang Li, Shenda Hong

The Effectiveness of Random Forgetting for Robust Generalization Vijaya Raghavan T Ramkumar, Bahram Zonooz, Elahe Arani

Continual Learning in the Presence of Spurious Correlations: Analyses and a Simple Baseline Donggyu Lee, Sangwon Jung, Taesup Moon

Unveiling the Unseen: Identifiable Clusters in Trained Depthwise Convolutional Kernels Zahra Babaiee, Peyman Kiasari, Daniela Rus, Radu Grosu

Rethinking Adversarial Policies: A Generalized Attack Formulation and Provable Defense in RL Xiangyu Liu, Souradip Chakraborty, Yanchao Sun, Furong Huang

HiGen: Hierarchical Graph Generative Networks Mahdi Karami

Local Graph Clustering with Noisy Labels Artur Back de Luca, Kimon Fountoulakis, Shenghao Yang

Accurate and Scalable Estimation of Epistemic Uncertainty for Graph Neural Networks Puja Trivedi, Mark Heimann, Rushil Anirudh, Danai Koutra, Jayaraman J. Thiagarajan

LUT-GEMM: Quantized Matrix Multiplication based on LUTs for Efficient Inference in Large-Scale Generative Language Models Gunho Park, baeseong park, Minsub Kim, Sungjae Lee, Jeonghoon Kim, Beomseok Kwon, Se Jung Kwon, Byeongwook Kim, Youngjoo Lee, Dongsoo Lee

Rotation Has Two Sides: Evaluating Data Augmentation for Deep One-class Classification Guodong Wang, Yunhong Wang, Xiuguo Bao, Di Huang

Investigating the Benefits of Projection Head for Representation Learning Yihao Xue, Eric Gan, Jiayi Ni, Siddharth Joshi, Baharan Mirzasoleiman

FedCDA: Federated Learning with Cross-rounds Divergence-aware Aggregation Haozhao Wang, Haoran Xu, Yichen Li, Yuan Xu, Ruixuan Li, Tianwei Zhang

Sin3DM: Learning a Diffusion Model from a Single 3D Textured Shape Rundi Wu, Ruoshi Liu, Carl Vondrick, Changxi Zheng

Image2Sentence based Asymmetrical Zero-shot Composed Image Retrieval Yongchao Du, Min Wang, Wengang Zhou, Shuping Hui, Houqiang Li

Poisoned Forgery Face: Towards Backdoor Attacks on Face Forgery Detection Jiawei Liang, Siyuan Liang, Aishan Liu, Xiaojun Jia, Junhao Kuang, Xiaochun Cao

A Characterization Theorem for Equivariant Networks with Point-wise Activations Marco Pacini, Xiaowen Dong, Bruno Lepri, Gabriele Santin

PolyVoice: Language Models for Speech to Speech Translation Qianqian Dong, Zhiying Huang, Qiao Tian, Chen Xu, Tom Ko, yunlong zhao, Siyuan Feng, Tang Li, Kexin Wang, Xuxin Cheng, Fengpeng Yue, Ye Bai, Xi Chen, Lu Lu, Zejun MA, Yuping Wang, Mingxuan Wang, Yuxuan Wang

Stable Neural Stochastic Differential Equations in Analyzing Irregular Time Series Data YongKyung Oh, Dongyoung Lim, Sungil Kim

Incentive-Aware Federated Learning with Training-Time Model Rewards Zhaoxuan Wu, Mohammad Mohammadi Amiri, Ramesh Raskar, Bryan Kian Hsiang Low

Social-Transmotion: Promptable Human Trajectory Prediction Saeed Saadatnejad, Yang Gao, Kaouther Messaoud, Alexandre Alahi

Parameter-Efficient Orthogonal Finetuning via Butterfly Factorization Weiyang Liu, Zeju Qiu, Yao Feng, Yuliang Xiu, Yuxuan Xue, Longhui Yu, Haiwen Feng, Zhen Liu, Juyeon Heo, Songyou Peng, Yandong Wen, Michael J Black, Adrian Weller, David Ha

Retrieval is Accurate Generation Bowen Cao, Deng Cai, Leyang Cui, Xuxin Cheng, Wei BI, Yuexian Zou, Shuming Shi

LayoutNUWA: Revealing the Hidden Layout Expertise of Large Language Models Zecheng Tang, Chenfei Wu, Juntao Li, Nan Duan

Toward Optimal Policy Population Growth in Two-Player Zero-Sum Games Stephen McAleer, John Banister Lanier, Kevin A. Wang, Pierre Baldi, Tuomas Sandholm, Roy Fox

Privacy Amplification for Matrix Mechanisms Christopher Choquette-Choo, Arun Ganesh, Thomas Steinke, Abhradeep Guha Thakurta

AttEXplore: Attribution for Explanation with model parameters eXploration Zhiyu Zhu, Huaming Chen, Jiayu Zhang, Xinyi Wang, Zhibo Jin, Jason Xue, Flora Salim

PINNsFormer: A Transformer-Based Framework For Physics-Informed Neural Networks Zhiyuan Zhao, Xueying Ding, B. Aditya Prakash

Graph Transformers on EHRs: Better Representation Improves Downstream Performance Raphael Poulain, Rahmatollah Beheshti

An Efficient Tester-Learner for Halfspaces Aravind Gollakota, Adam Klivans, Konstantinos Stavropoulos, Arsen Vasilyan

Implicit Gaussian process representation of vector fields over arbitrary latent manifolds Robert Peach, Matteo Vinao-Carl, Nir Grossman, Michael David, Emma-Jane Mallas, David Sharp, Paresh Malhotra, Pierre Vandergheynst, Adam Gosztolai

DMBP: Diffusion model-based predictor for robust offline reinforcement learning against state observation perturbations Zhihe Yang, Yunjian Xu

Achieving Human Parity in Content-Grounded Datasets Generation Asaf Yehudai, Boaz Carmeli, Yosi Mass, Ofir Arviv, Nathaniel Mills, Eyal Shnarch, Leshem Choshen

COLLIE: Systematic Construction of Constrained Text Generation Tasks Shunyu Yao, Howard Chen, Austin Hanjie, Runzhe Yang, Karthik Narasimhan

A Good Learner can Teach Better: Teacher-Student Collaborative Knowledge Distillation Ayan Sengupta, Shantanu Dixit, Md Shad Akhtar, Tanmoy Chakraborty

TimeMixer: Decomposable Multiscale Mixing for Time Series Forecasting Shiyu Wang, Haixu Wu, Xiaoming Shi, Tengge Hu, Huakun Luo, Lintao Ma, James Zhang, JUN ZHOU

IDEAL: Influence-Driven Selective Annotations Empower In-Context Learners in Large Language Models Shaokun Zhang, Xiaobo Xia, Zhaoqing Wang, Ling-Hao Chen, Jiale Liu, Qingyun Wu, Tongliang Liu

Hybrid Sharing for Multi-Label Image Classification Zihao Yin, Chen Gan, Kelei He, Yang Gao, Junfeng Zhang

Masked Structural Growth for 2x Faster Language Model Pre-training Yiqun Yao, Zheng Zhang, Jing Li, Yequan Wang

Learning with Language-Guided State Abstractions Andi Peng, Ilia Sucholutsky, Belinda Li, Theodore Sumers, Thomas L. Griffiths, Jacob Andreas, Julie Shah

On the Learnability of Watermarks for Language Models Chenchen Gu, XIANG LI, Percy Liang, Tatsunori Hashimoto

Spatio-Temporal Approximation: A Training-Free SNN Conversion for Transformers Yizhou Jiang, Kunlin Hu, Tianren Zhang, Haichuan Gao, Yuqian Liu, Ying Fang, Feng Chen

GeoLLM: Extracting Geospatial Knowledge from Large Language Models Rohin Manvi, Samar Khanna, Gengchen Mai, Marshall Burke, David Lobell, Stefano Ermon

Dynamic Discounted Counterfactual Regret Minimization Hang Xu, Kai Li, Haobo Fu, QIANG FU, Junliang Xing, Jian Cheng

Tight Rates in Supervised Outlier Transfer Learning Mohammadreza Mousavi Kalan, Samory Kpotufe

Invariance-based Learning of Latent Dynamics Kai Lagemann, Christian Lagemann, Sach Mukherjee

Motif: Intrinsic Motivation from Artificial Intelligence Feedback Martin Klissarov, Pierluca D'Oro, Shagun Sodhani, Roberta Raileanu, Pierre-Luc Bacon, Pascal Vincent, Amy Zhang, Mikael Henaff

Decomposed Diffusion Sampler for Accelerating Large-Scale Inverse Problems Hyungjin Chung, Suhyeon Lee, Jong Chul YE

Sample-Efficient Multi-Agent RL: An Optimization Perspective Nuoya Xiong, Zhihan Liu, Zhaoran Wang, Zhuoran Yang

Hypothesis Search: Inductive Reasoning with Language Models Ruocheng Wang, Eric Zelikman, Gabriel Poesia, Yewen Pu, Nick Haber, Noah Goodman

Steve-Eye: Equipping LLM-based Embodied Agents with Visual Perception in Open Worlds Sipeng Zheng, jiazheng liu, Yicheng Feng, Zongqing Lu

RTFS-Net: Recurrent Time-Frequency Modelling for Efficient Audio-Visual Speech Separation Samuel Pegg, Kai Li, Xiaolin Hu

CO2: Efficient Distributed Training with Full Communication-Computation Overlap Weigao Sun, Qin Zhen, Weixuan Sun, Shidi Li, Dong Li, Xuyang Shen, Yu Qiao, Yiran Zhong

Fantastic Generalization Measures are Nowhere to be Found Michael Gastpar, Ido Nachum, Jonathan Shafer, Thomas Weinberger

FedCompass: Efficient Cross-Silo Federated Learning on Heterogeneous Client Devices Using a Computing Power-Aware Scheduler Zilinghan Li, Pranshu Chaturvedi, Shilan He, Han Chen, Gagandeep Singh, Volodymyr Kindratenko, Eliu Huerta, Kibaek Kim, Ravi Madduri

An improved analysis of per-sample and per-update clipping in federated learning Bo Li, Xiaowen Jiang, Mikkel N. Schmidt, Tommy Sonne Alstrøm, Sebastian Stich

Fixed-Budget Differentially Private Best Arm Identification Zhirui Chen, P. N. Karthik, Yeow Meng Chee, Vincent Tan

Compose and Conquer: Diffusion-Based 3D Depth Aware Composable Image Synthesis Jonghyun Lee, Hansam Cho, YoungJoon Yoo, Seoung Bum Kim, Yonghyun Jeong

Identifying Representations for Intervention Extrapolation Sorawit (James) Saengkyongam, Elan Rosenfeld, Pradeep K Ravikumar, Niklas Pfister, Jonas Peters

EquiformerV2: Improved Equivariant Transformer for Scaling to Higher-Degree Representations Yi-Lun Liao, Brandon Wood, Abhishek Das, Tess Smidt

HyperAttention: Long-context Attention in Near-Linear Time Insu Han, Rajesh Jayaram, Amin Karbasi, Vahab Mirrokni, David Woodruff, Amir Zandieh

Magnushammer: A Transformer-Based Approach to Premise Selection Maciej Mikuła, Szymon Tworkowski, Szymon Antoniak, Bartosz Piotrowski, Qiaochu Jiang, Jin Zhou, Christian Szegedy, Łukasz Kuciński, Piotr Miłoś, Yuhuai Wu

A Graph is Worth 1-bit Spikes: When Graph Contrastive Learning Meets Spiking Neural Networks Jintang Li, Huizhe Zhang, Ruofan Wu, Zulun Zhu, Baokun Wang, Changhua Meng, Zibin Zheng, Liang Chen

Towards Codable Watermarking for Injecting Multi-Bits Information to LLMs Lean Wang, Wenkai Yang, Deli Chen, Hao Zhou, Yankai Lin, Fandong Meng, Jie Zhou, Xu Sun

Bounds on Representation-Induced Confounding Bias for Treatment Effect Estimation Valentyn Melnychuk, Dennis Frauen, Stefan Feuerriegel

Generating Pragmatic Examples to Train Neural Program Synthesizers Saujas Vaduguru, Daniel Fried, Yewen Pu

Meaning Representations from Trajectories in Autoregressive Models Tian Yu Liu, Matthew Trager, Alessandro Achille, Pramuditha Perera, Luca Zancato, Stefano Soatto

Learning Mean Field Games on Sparse Graphs: A Hybrid Graphex Approach Christian Fabian, Kai Cui, Heinz Koeppl

A Recipe for Improved Certifiable Robustness Kai Hu, Klas Leino, Zifan Wang, Matt Fredrikson

Jointly-Learned Exit and Inference for a Dynamic Neural Network Florence Regol, Joud Chataoui, Mark Coates

A Dynamical View of the Question of Why Mehdi Fatemi, Sindhu Chatralinganadoddi Mariyappa Gowda

Let's Verify Step by Step Hunter Lightman, Vineet Kosaraju, Yuri Burda, Harrison Edwards, Bowen Baker, Teddy Lee, Jan Leike, John Schulman, Ilya Sutskever, Karl Cobbe

Retrieval-based Disentangled Representation Learning with Natural Language Supervision Jiawei Zhou, Xiaoguang Li, Lifeng Shang, Xin Jiang, Qun Liu, Lei Chen

RetroBridge: Modeling Retrosynthesis with Markov Bridges Ilia Igashov, Arne Schneuing, Marwin Segler, Michael Bronstein, Bruno Correia

Ins-DetCLIP: Aligning Detection Model to Follow Human-Language Instruction Renjie Pi, Lewei Yao, Jianhua Han, Xiaodan Liang, Wei Zhang, Hang Xu

Differentially Private SGD Without Clipping Bias: An Error-Feedback Approach Xinwei Zhang, Zhiqi Bu, Steven Wu, Mingyi Hong

Learning No-Regret Sparse Generalized Linear Models with Varying Observation(s) Diyang Li, Charles Ling, Zhiqiang Xu, Huan Xiong, Bin Gu

InfoBatch: Lossless Training Speed Up by Unbiased Dynamic Data Pruning Ziheng Qin, Kai Wang, Zangwei Zheng, Jianyang Gu, Xiangyu Peng, Zhaopan Xu, Zhou Daquan, Lei Shang, Baigui Sun, Xuansong Xie, Yang You

On the Stability of Expressive Positional Encodings for Graphs Yinan Huang, William Lu, Joshua Robinson, Yu Yang, Muhan Zhang, Stefanie Jegelka, Pan Li

Dropout Enhanced Bilevel Training Peiran Yu, Junyi Li, Heng Huang

Improved Probabilistic Image-Text Representations Sanghyuk Chun

MVSFormer++: Revealing the Devil in Transformer's Details for Multi-View Stereo chenjie cao, xinlin ren, Yanwei Fu

MVDream: Multi-view Diffusion for 3D Generation Yichun Shi, Peng Wang, Jianglong Ye, Long Mai, Kejie Li, Xiao Yang

LLM Blueprint: Enabling Text-to-Image Generation with Complex and Detailed Prompts Hanan Gani, Shariq Bhat, Muzammal Naseer, Salman Khan, Peter Wonka

Learning Hierarchical Image Segmentation For Recognition and By Recognition Tsung-Wei Ke, Sangwoo Mo, Stella Yu

Adversarial Training on Purification (AToP): Advancing Both Robustness and Generalization Guang Lin, Chao Li, Jianhai Zhang, Toshihisa Tanaka, Qibin Zhao

Memorization in Self-Supervised Learning Improves Downstream Generalization Wenhao Wang, Muhammad Ahmad Kaleem, Adam Dziedzic, Michael Backes, Nicolas Papernot, Franziska Boenisch

MBR and QE Finetuning: Training-time Distillation of the Best and Most Expensive Decoding Methods Mara Finkelstein, Markus Freitag

ASID: Active Exploration for System Identification in Robotic Manipulation Marius Memmel, Andrew Wagenmaker, Chuning Zhu, Dieter Fox, Abhishek Gupta

Experimental Design for Multi-Channel Imaging via Task-Driven Feature Selection Stefano Blumberg, Paddy Slator, Daniel Alexander

Cauchy-Schwarz Divergence Information Bottleneck for Regression Shujian Yu, Xi Yu, Sigurd Løkse, Robert Jenssen, Jose Principe

A Hierarchical Bayesian Model for Few-Shot Meta Learning Minyoung Kim, Timothy Hospedales

CRAFT: Customizing LLMs by Creating and Retrieving from Specialized Toolsets Lifan Yuan, Yangyi Chen, Xingyao Wang, Yi Fung, Hao Peng, Heng Ji

Learning Hierarchical Polynomials with Three-Layer Neural Networks Zihao Wang, Eshaan Nichani, Jason Lee

Gen-Z: Generative Zero-Shot Text Classification with Contextualized Label Descriptions Sachin Kumar, Chan Young Park, Yulia Tsvetkov

Evaluating Large Language Models at Evaluating Instruction Following Zhiyuan Zeng, Jiatong Yu, Tianyu Gao, Yu Meng, Tanya Goyal, Danqi Chen

Efficient ConvBN Blocks for Transfer Learning and Beyond Kaichao You, Guo Qin, Anchang Bao, Meng Cao, Ping Huang, Jiulong Shan, Mingsheng Long

Backdoor Federated Learning by Poisoning Backdoor-Critical Layers Haomin Zhuang, Mingxian Yu, Hao Wang, Yang Hua, Jian Li, Xu Yuan

Leave-one-out Distinguishability in Machine Learning Jiayuan Ye, Anastasia Borovykh, Soufiane Hayou, Reza Shokri

Towards Green AI in Fine-tuning Large Language Models via Adaptive Backpropagation Kai Huang, Hanyun Yin, Heng Huang, Wei Gao

MAmmoTH: Building Math Generalist Models through Hybrid Instruction Tuning Xiang Yue, Xingwei Qu, Ge Zhang, Yao Fu, Wenhao Huang, Huan Sun, Yu Su, Wenhu Chen

Encoding Unitig-level Assembly Graphs with Heterophilous Constraints for Metagenomic Contigs Binning Hansheng Xue, Vijini Mallawaarachchi, Lexing Xie, Vaibhav Rajan

Self-contradictory Hallucinations of Large Language Models: Evaluation, Detection and Mitigation Niels Mündler, Jingxuan He, Slobodan Jenko, Martin Vechev

Revisiting the Last-Iterate Convergence of Stochastic Gradient Methods Zijian Liu, Zhengyuan Zhou

Pre-training with Random Orthogonal Projection Image Modeling Maryam Haghighat, Peyman Moghadam, Shaheer Mohamed, Piotr Koniusz

Matrix Manifold Neural Networks++ Xuan Son Nguyen, Yang, Aymeric Histace

Neuroformer: Multimodal and Multitask Generative Pretraining for Brain Data Antonis Antoniades, Yiyi Yu, Joe Canzano, William Wang, Spencer Smith

ViLMA: A Zero-Shot Benchmark for Linguistic and Temporal Grounding in Video-Language Models İlker Kesen, Andrea Pedrotti, Mustafa Dogan, Michele Cafagna, Emre Can Acikgoz, Letitia Parcalabescu, Iacer Calixto, Anette Frank, Albert Gatt, Aykut Erdem, Erkut Erdem

$\alpha$TC-VAE: On the relationship between Disentanglement and Diversity Cristian Meo, Louis Mahon, Anirudh Goyal, Justin Dauwels

SLiMe: Segment Like Me Aliasghar Khani, Saeid Asgari, Aditya Sanghi, Ali Mahdavi Amiri, Ghassan Hamarneh

REFACTOR: Learning to Extract Theorems from Proofs Jin Zhou, Yuhuai Wu, Qiyang Li, Roger Grosse

Llemma: An Open Language Model for Mathematics Zhangir Azerbayev, Hailey Schoelkopf, Keiran Paster, Marco Dos Santos, Stephen McAleer, Qiaochu Jiang, Jia Deng, Stella R Biderman, Sean Welleck

Why is SAM Robust to Label Noise? Christina Baek, Zico Kolter, Aditi Raghunathan

Sample-Efficiency in Multi-Batch Reinforcement Learning: The Need for Dimension-Dependent Adaptivity Emmeran Johnson, Ciara Pike-Burke, Patrick Rebeschini

Exploring Weight Balancing on Long-Tailed Recognition Problem Naoya Hasegawa, Issei Sato

Fourier Transporter: Bi-Equivariant Robotic Manipulation in 3D Haojie Huang, Owen Howell, Dian Wang, Xupeng Zhu, Robert Platt, Robin Walters

Learning Decentralized Partially Observable Mean Field Control for Artificial Collective Behavior Kai Cui, Sascha Hauck, Christian Fabian, Heinz Koeppl

Implicit regularization of deep residual networks towards neural ODEs Pierre Marion, Yu-Han Wu, Michael Sander, Gérard Biau

Efficient Planning with Latent Diffusion Wenhao Li

Information Bottleneck Analysis of Deep Neural Networks via Lossy Compression Ivan Butakov, Aleksandr Tolmachev, Sofia Malanchuk, Anna Neopryatnaya, Alexey Frolov, Kirill Andreev

Layer-wise linear mode connectivity Linara Adilova, Maksym Andriushchenko, Michael Kamp, Asja Fischer, Martin Jaggi

DittoGym: Learning to Control Soft Shape-Shifting Robots Suning Huang, Boyuan Chen, Huazhe Xu, Vincent Sitzmann

Learning to Act from Actionless Videos through Dense Correspondences Po-Chen Ko, Jiayuan Mao, Yilun Du, Shao-Hua Sun, Joshua B Tenenbaum

Kosmos-G: Generating Images in Context with Multimodal Large Language Models Xichen Pan, Li Dong, Shaohan Huang, Zhiliang Peng, Wenhu Chen, Furu Wei

SOTOPIA: Interactive Evaluation for Social Intelligence in Language Agents Xuhui Zhou, Hao Zhu, Leena Mathur, Ruohong Zhang, Haofei Yu, Zhengyang Qi, Louis-Philippe Morency, Yonatan Bisk, Daniel Fried, Graham Neubig, Maarten Sap

RAPPER: Reinforced Rationale-Prompted Paradigm for Natural Language Explanation in Visual Question Answering Kai-Po Chang, Chi-Pin Huang, Wei-Yuan Cheng, Fu-En Yang, Chien-Yi Wang, Yung-Hsuan Lai, Yu-Chiang Frank Wang

MOTOR: A Time-to-Event Foundation Model For Structured Medical Records Ethan Steinberg, Jason Fries, Yizhe Xu, Nigam Shah

Get more for less: Principled Data Selection for Warming Up Fine-Tuning in LLMs Feiyang Kang, Hoang Anh Just, Yifan Sun, Himanshu Jahagirdar, Yuanzhi Zhang, Rongxing Du, Anit Kumar Sahu, Ruoxi Jia

A path-norm toolkit for modern networks: consequences, promises and challenges Antoine Gonon, Nicolas Brisebarre, Elisa Riccietti, Rémi Gribonval

PubDef: Defending Against Transfer Attacks From Public Models Chawin Sitawarin, Jaewon Chang, David Huang, Wesson Altoyan, David Wagner

DQ-LoRe: Dual Queries with Low Rank Approximation Re-ranking for In-Context Learning Jing Xiong, Zixuan Li, Chuanyang Zheng, Zhijiang Guo, Yichun Yin, Enze Xie, Zhicheng YANG, Qingxing Cao, Haiming Wang, Xiongwei Han, Jing Tang, Chengming Li, Xiaodan Liang

Continuous-Multiple Image Outpainting in One-Step via Positional Query and A Diffusion-based Approach Shaofeng Zhang, Jinfa Huang, Qiang Zhou, zhibin wang, Fan Wang, Jiebo Luo, Junchi Yan

Towards Robust and Efficient Cloud-Edge Elastic Model Adaptation via Selective Entropy Distillation Yaofo Chen, Shuaicheng Niu, Yaowei Wang, Shoukai Xu, Hengjie Song, Mingkui Tan

Towards Optimal Feature-Shaping Methods for Out-of-Distribution Detection Qinyu Zhao, Ming Xu, Kartik Gupta, Akshay Asthana, Liang Zheng, Stephen Gould

ArchLock: Locking DNN Transferability at the Architecture Level with a Zero-Cost Binary Predictor Tong Zhou, Shaolei Ren, Xiaolin Xu

You Only Query Once: An Efficient Label-Only Membership Inference Attack Yutong Wu, Han Qiu, Shangwei Guo, Jiwei Li, Tianwei Zhang

PILOT: An $\mathcal{O}(1/K)$-Convergent Approach for Policy Evaluation with Nonlinear Function Approximation Zhuqing Liu, Xin Zhang, Jia (Kevin) Liu, Zhengyuan Zhu, Songtao Lu

Improving Offline RL by Blending Heuristics Sinong Geng, Aldo Pacchiano, Andrey Kolobov, Ching-An Cheng

Hybrid LLM: Cost-Efficient and Quality-Aware Query Routing Dujian Ding, Ankur Mallick, Chi Wang, Robert Sim, Subhabrata Mukherjee, Victor Rühle, Laks Lakshmanan, Ahmed H Awadallah

Horizon-free Reinforcement Learning in Adversarial Linear Mixture MDPs Kaixuan Ji, Qingyue Zhao, Jiafan He, Weitong ZHANG, Quanquan Gu

Chain of Hindsight aligns Language Models with Feedback Hao Liu, Carmelo Sferrazza, Pieter Abbeel

A Cognitive Model for Learning Abstract Relational Structures from Memory-based Decision-Making Tasks Haruo Hosoya

Rethinking Channel Dependence for Multivariate Time Series Forecasting: Learning from Leading Indicators Lifan Zhao, Yanyan Shen

Towards Transparent Time Series Forecasting Krzysztof Kacprzyk, Tennison Liu, Mihaela van der Schaar

Towards Assessing and Benchmarking Risk-Return Tradeoff of Off-Policy Evaluation Haruka Kiyohara, Ren Kishimoto, Kosuke Kawakami, Ken Kobayashi, Kazuhide Nakata, Yuta Saito

Linear Log-Normal Attention with Unbiased Concentration Yury Nahshan, Joseph Kampeas, Emir Haleva

Ring-A-Bell! How Reliable are Concept Removal Methods For Diffusion Models? Yu-Lin Tsai, Chia-Yi Hsu, Chulin Xie, Chih-Hsun Lin, Jia You Chen, Bo Li, Pin-Yu Chen, Chia-Mu Yu, Chun-Ying Huang

Fair Classifiers that Abstain without Harm Tongxin Yin, Jean-Francois Ton, Ruocheng Guo, Yuanshun Yao, Mingyan Liu, Yang Liu

Diffusion-TS: Interpretable Diffusion for General Time Series Generation Xinyu Yuan, Yan Qiao

Tailoring Self-Rationalizers with Multi-Reward Distillation Sahana Ramnath, Brihi Joshi, Skyler Hallinan, Ximing Lu, Liunian Li, Aaron Chan, Jack Hessel, Yejin Choi, Xiang Ren

DNABERT-2: Efficient Foundation Model and Benchmark For Multi-Species Genomes Zhihan Zhou, Yanrong Ji, Weijian Li, Pratik Dutta, Ramana Davuluri, Han Liu

Towards Diverse Behaviors: A Benchmark for Imitation Learning with Human Demonstrations Xiaogang Jia, Denis Blessing, Xinkai Jiang, Moritz Reuss, Atalay Donat, Rudolf Lioutikov, Gerhard Neumann

CoLiDE: Concomitant Linear DAG Estimation Seyed Saman Saboksayr, Gonzalo Mateos, Mariano Tepper

A 2-Dimensional State Space Layer for Spatial Inductive Bias Ethan Baron, Itamar Zimerman, Lior Wolf

Boosting of Thoughts: Trial-and-Error Problem Solving with Large Language Models Sijia Chen, Baochun Li, Di Niu

The Blessing of Randomness: SDE Beats ODE in General Diffusion-based Image Editing Shen Nie, Hanzhong Guo, Cheng Lu, Yuhao Zhou, Chenyu Zheng, Chongxuan Li

ACRF: Compressing Explicit Neural Radiance Fields via Attribute Compression Guangchi Fang, Qingyong Hu, Longguang Wang, Yulan Guo

Towards Poisoning Fair Representations Tianci Liu, Haoyu Wang, Feijie Wu, Hengtong Zhang, Pan Li, Lu Su, Jing Gao

Efficient Score Matching with Deep Equilibrium Layers Yuhao Huang, Qingsong Wang, Akwum Onwunta, Bao Wang

H2O-SDF: Two-phase Learning for 3D Indoor Reconstruction using Object Surface Fields Minyoung Park, MIRAE DO, Yeon Jae Shin, Jaeseok Yoo, Jongkwang Hong, Joongrock Kim, Chul Lee

ImageNet-OOD: Deciphering Modern Out-of-Distribution Detection Algorithms William Yang, Byron Zhang, Olga Russakovsky

SYMBOL: Generating Flexible Black-Box Optimizers through Symbolic Equation Learning Jiacheng Chen, Zeyuan Ma, Hongshu Guo, Yining Ma, Jie Zhang, Yue-Jiao Gong

Neural Language of Thought Models Yi-Fu Wu, Minseung Lee, Sungjin Ahn

Towards a statistical theory of data selection under weak supervision Germain Kolossov, Andrea Montanari, Pulkit Tandon

Causal Fairness under Unobserved Confounding: A Neural Sensitivity Framework Maresa Schröder, Dennis Frauen, Stefan Feuerriegel

Counting Graph Substructures with Graph Neural Networks Charilaos Kanatsoulis, Alejandro Ribeiro

InternVid: A Large-scale Video-Text Dataset for Multimodal Understanding and Generation Yi Wang, Yinan He, Yizhuo Li, Kunchang Li, Jiashuo Yu, Xin Ma, Xinhao Li, Guo Chen, Xinyuan Chen, Yaohui Wang, Ping Luo, Ziwei Liu, Yali Wang, Limin Wang, Yu Qiao

Risk Bounds of Accelerated SGD for Overparameterized Linear Regression Xuheng Li, Yihe Deng, Jingfeng Wu, Dongruo Zhou, Quanquan Gu

Decodable and Sample Invariant Continuous Object Encoder Dehao Yuan, Furong Huang, Cornelia Fermuller, Yiannis Aloimonos

Scaling Laws for Sparsely-Connected Foundation Models Elias Frantar, Carlos Riquelme Ruiz, Neil Houlsby, Dan Alistarh, Utku Evci

Looped Transformers are Better at Learning Learning Algorithms Liu Yang, Kangwook Lee, Robert Nowak, Dimitris Papailiopoulos

Query-Dependent Prompt Evaluation and Optimization with Offline Inverse RL Hao Sun, Alihan Hüyük, Mihaela van der Schaar

PAE: Reinforcement Learning from External Knowledge for Efficient Exploration Zhe Wu, Haofei Lu, Junliang Xing, You Wu, Renye Yan, Yaozhong Gan, Yuanchun Shi

Local Search GFlowNets Minsu Kim, Taeyoung Yun, Emmanuel Bengio, Dinghuai Zhang, Yoshua Bengio, Sungsoo Ahn, Jinkyoo Park

Constructing Adversarial Examples for Vertical Federated Learning: Optimal Client Corruption through Multi-Armed Bandit Duanyi YAO, Songze Li, Ye XUE, Jin Liu

Massively Scalable Inverse Reinforcement Learning in Google Maps Matt Barnes, Matthew Abueg, Oliver Lange, Matt Deeds, Jason Trader, Denali Molitor, Markus Wulfmeier, Shawn O'Banion

SNIP: Bridging Mathematical Symbolic and Numeric Realms with Unified Pre-training Kazem Meidani, Parshin Shojaee, Chandan Reddy, Amir Barati Farimani

Unsupervised Order Learning Seon-Ho Lee, Nyeong-Ho Shin, Chang-Su Kim

A General Framework for User-Guided Bayesian Optimization Carl Hvarfner, Frank Hutter, Luigi Nardi

Tell Your Model Where to Attend: Post-hoc Attention Steering for LLMs Qingru Zhang, Chandan Singh, Liyuan Liu, Xiaodong Liu, Bin Yu, Jianfeng Gao, Tuo Zhao

Fast Ensembling with Diffusion Schrödinger Bridge Hyunsu Kim, Jongmin Yoon, Juho Lee

On the Power of the Weisfeiler-Leman Test for Graph Motif Parameters Matthias Lanzinger, Pablo Barcelo

PBADet: A One-Stage Anchor-Free Approach for Part-Body Association Zhongpai Gao, Huayi Zhou, Abhishek Sharma, Meng Zheng, Benjamin Planche, Terrence Chen, Ziyan Wu

EX-Graph: A Pioneering Dataset Bridging Ethereum and X Qian Wang, Zhen Zhang, Zemin Liu, Shengliang Lu, Bingqiao Luo, Bingsheng He

Neural Network-Based Score Estimation in Diffusion Models: Optimization and Generalization Yinbin Han, Meisam Razaviyayn, Renyuan Xu

Grounded Object-Centric Learning Avinash Kori, Francesco Locatello, Fabio De Sousa Ribeiro, Francesca Toni, Ben Glocker

A Mutual Information Perspective on Federated Contrastive Learning Christos Louizos, Matthias Reisser, Denis Korzhenkov

Improving Domain Generalization with Domain Relations Huaxiu Yao, Xinyu Yang, Xinyi Pan, Shengchao Liu, Pang Wei Koh, Chelsea Finn

Thin-Shell Object Manipulations With Differentiable Physics Simulations Yian Wang, Juntian Zheng, Zhehuan Chen, Zhou Xian, Gu Zhang, Chao Liu, Chuang Gan

FedTrans: Client-Transparent Utility Estimation for Robust Federated Learning Mingkun Yang, Ran Zhu, Qing Wang, Jie Yang

Variance Reduced Halpern Iteration for Finite-Sum Monotone Inclusions Xufeng Cai, Ahmet Alacaoglu, Jelena Diakonikolas

Pseudo-Generalized Dynamic View Synthesis from a Video Xiaoming Zhao, R Colburn, Fangchang Ma, MIGUEL ANGEL BAUTISTA, Joshua Susskind, Alex Schwing

Overthinking the Truth: Understanding how Language Models Process False Demonstrations Danny Halawi, Jean-Stanislas Denain, Jacob Steinhardt

Det-CGD: Compressed Gradient Descent with Matrix Stepsizes for Non-Convex Optimization Hanmin Li, Avetik Karagulyan, Peter Richtarik

The Cost of Scaling Down Large Language Models: Reducing Model Size Affects Memory before In-context Learning Tian Jin, Nolan Clement, Xin Dong, Vaishnavh Nagarajan, Michael Carbin, Jonathan Ragan-Kelley, Gintare Karolina Dziugaite

Lifting Architectural Constraints of Injective Flows Peter Sorrenson, Felix Draxler, Armand Rousselot, Sander Hummerich, Lea Zimmermann, Ullrich Koethe

On Bias-Variance Alignment in Deep Models Lin Chen, Michal Lukasik, Wittawat Jitkrittum, Chong You, Sanjiv Kumar

Safe Collaborative Filtering Riku Togashi, Tatsushi Oka, Naoto Ohsaka, Tetsuro Morimura

Towards Faithful Explanations: Boosting Rationalization with Shortcuts Discovery Linan Yue, Qi Liu, Yichao Du, Li Wang, Weibo Gao, Yanqing An

SKILL-MIX: a Flexible and Expandable Family of Evaluations for AI Models Dingli Yu, Simran Kaur, Arushi Gupta, Jonah Brown-Cohen, Anirudh Goyal, Sanjeev Arora

MetaTool Benchmark for Large Language Models: Deciding Whether to Use Tools and Which to Use Yue Huang, Jiawen Shi, Yuan Li, Chenrui Fan, Siyuan Wu, Qihui Zhang, Yixin Liu, Pan Zhou, Yao Wan, Neil Gong, Lichao Sun

Time Travel in LLMs: Tracing Data Contamination in Large Language Models Shahriar Golchin, Mihai Surdeanu

DORSal: Diffusion for Object-centric Representations of Scenes $\textit{et al.}$ Allan Jabri, Sjoerd van Steenkiste, Emiel Hoogeboom, Mehdi S. M. Sajjadi, Thomas Kipf

Amortizing intractable inference in large language models Edward Hu, Moksh Jain, Eric Elmoznino, Younesse Kaddar, Guillaume Lajoie, Yoshua Bengio, Nikolay Malkin

A Versatile Causal Discovery Framework to Allow Causally-Related Hidden Variables Xinshuai Dong, Biwei Huang, Ignavier Ng, Xiangchen Song, Yujia Zheng, Songyao Jin, Roberto Legaspi, Peter Spirtes, Kun Zhang

Communication-Efficient Gradient Descent-Accent Methods for Distributed Variational Inequalities: Unified Analysis and Local Updates Siqi Zhang, Sayantan Choudhury, Sebastian Stich, Nicolas Loizou

Algorithms for Caching and MTS with reduced number of predictions Karim Ahmed Abdel Sadek, Marek Elias

When Semantic Segmentation Meets Frequency Aliasing Linwei Chen, Lin Gu, Ying Fu

EControl: Fast Distributed Optimization with Compression and Error Control Yuan Gao, Rustem Islamov, Sebastian Stich

Masked Audio Generation using a Single Non-Autoregressive Transformer Alon Ziv, Itai Gat, Gael Le Lan, Tal Remez, Felix Kreuk, Jade Copet, Alexandre Défossez, Gabriel Synnaeve, Yossi Adi

Designing Skill-Compatible AI: Methodologies and Frameworks in Chess KARIM HAMADE, Reid McIlroy-Young, Siddhartha Sen, Jon Kleinberg, Ashton Anderson

Multisize Dataset Condensation Yang He, Lingao Xiao, Joey Tianyi Zhou, Ivor Tsang

Large Multilingual Models Pivot Zero-Shot Multimodal Learning across Languages Jinyi Hu, Yuan Yao, Chongyi Wang, SHAN WANG, Yinxu Pan, Qianyu Chen, Tianyu Yu, Hanghao Wu, Yue Zhao, Haoye Zhang, Xu Han, Yankai Lin, Jiao Xue, dahai li, Zhiyuan Liu, Maosong Sun

Incremental Randomized Smoothing Certification Shubham Dipak Ugare, Tarun Suresh, Debangshu Banerjee, Gagandeep Singh, Sasa Misailovic

Benign Overfitting and Grokking in ReLU Networks for XOR Cluster Data Zhiwei Xu, Yutong Wang, Spencer Frei, Gal Vardi, Wei Hu

Explaining Time Series via Contrastive and Locally Sparse Perturbations Zichuan Liu, Yingying ZHANG, Tianchun Wang, Zefan Wang, Dongsheng Luo, Mengnan Du, Min Wu, Yi Wang, Chunlin Chen, Lunting Fan, Qingsong Wen

Stochastic Modified Equations and Dynamics of Dropout Algorithm Zhongwang Zhang, Yuqing Li, Tao Luo, Zhiqin Xu

RECOMP: Improving Retrieval-Augmented LMs with Context Compression and Selective Augmentation Fangyuan Xu, Weijia Shi, Eunsol Choi

Likelihood Training of Cascaded Diffusion Models via Hierarchical Volume-preserving Maps Henry Li, Ronen Basri, Yuval Kluger

Towards Faithful XAI Evaluation via Generalization-Limited Backdoor Watermark Mengxi Ya, Yiming Li, Tao Dai, Bin Wang, Yong Jiang, Shu-Tao Xia

PanoDiffusion: 360-degree Panorama Outpainting via Diffusion Tianhao Wu, Chuanxia Zheng, Tat-Jen Cham

PandaLM: An Automatic Evaluation Benchmark for LLM Instruction Tuning Optimization Yidong Wang, Zhuohao Yu, Wenjin Yao, Zhengran Zeng, Linyi Yang, Cunxiang Wang, Hao Chen, Chaoya Jiang, Rui Xie, Jindong Wang, Xing Xie, Wei Ye, Shikun Zhang, Yue Zhang

IRAD: Implicit Representation-driven Image Resampling against Adversarial Attacks Yue Cao, Tianlin Li, Xiaofeng Cao, Ivor Tsang, Yang Liu, Qing Guo

Pre-training with Synthetic Data Helps Offline Reinforcement Learning Zecheng Wang, Che Wang, Zixuan Dong, Keith Ross

Grounding Language Plans in Demonstrations Through Counterfactual Perturbations Yanwei Wang, Johnson (Tsun-Hsuan) Wang, Jiayuan Mao, Michael Hagenow, Julie Shah

Distributionally Robust Optimization with Bias and Variance Reduction Ronak Mehta, Vincent Roulet, Krishna Pillutla, Zaid Harchaoui

Provable Robust Watermarking for AI-Generated Text Xuandong Zhao, Prabhanjan Ananth, Lei Li, Yu-Xiang Wang

On the Analysis of GAN-based Image-to-Image Translation with Gaussian Noise Injection Chaohua Shi, Kexin Huang, Lu Gan, Hongqing Liu, Mingrui Zhu, Nannan Wang, Xinbo Gao

On the Over-Memorization During Natural, Robust and Catastrophic Overfitting Runqi Lin, Chaojian Yu, Bo Han, Tongliang Liu

On the Foundations of Shortcut Learning Katherine Hermann, Hossein Mobahi, Thomas FEL, Michael Mozer

Accelerating Data Generation for Neural Operators via Krylov Subspace Recycling Hong Wang, Zhongkai Hao, Jie Wang, Zijie Geng, Zhen Wang, Bin Li, Feng Wu

Talk like a Graph: Encoding Graphs for Large Language Models Bahare Fatemi, Jonathan Halcrow, Bryan Perozzi

Efficient Integrators for Diffusion Generative Models Kushagra Pandey, Maja Rudolph, Stephan Mandt

Supervised Knowledge Makes Large Language Models Better In-context Learners Linyi Yang, Shuibai Zhang, Zhuohao Yu, Guangsheng Bao, Yidong Wang, Jindong Wang, Ruochen Xu, Wei Ye, Xing Xie, Weizhu Chen, Yue Zhang

Monte Carlo guided Denoising Diffusion models for Bayesian linear inverse problems. Gabriel Cardoso, Yazid Janati el idrissi, Sylvain Le Corff, Eric Moulines

Benchmarking and Improving Generator-Validator Consistency of Language Models XIANG LI, Vaishnavi Shrivastava, Siyan Li, Tatsunori Hashimoto, Percy Liang

FairSeg: A Large-Scale Medical Image Segmentation Dataset for Fairness Learning Using Segment Anything Model with Fair Error-Bound Scaling Yu Tian, Min Shi, Yan Luo, Ava Kouhana, Tobias Elze, Mengyu Wang

Representation Deficiency in Masked Language Modeling Yu Meng, Jitin Krishnan, Sinong Wang, Qifan Wang, Yuning Mao, Han Fang, Marjan Ghazvininejad, Jiawei Han, Luke Zettlemoyer

Learning semilinear neural operators: A unified recursive framework for prediction and data assimilation. Ashutosh Singh, Ricardo Borsoi, Deniz Erdogmus, Tales Imbiriba

Neural Architecture Retrieval Xiaohuan Pei, Yanxi Li, Minjing Dong, Chang Xu

Fixed Non-negative Orthogonal Classifier: Inducing Zero-mean Neural Collapse with Feature Dimension Separation Hoyong Kim, Kangil Kim

Does CLIP’s generalization performance mainly stem from high train-test similarity? Prasanna Mayilvahanan, Thaddäus Wiedemer, Evgenia Rusak, Matthias Bethge, Wieland Brendel

Multi-granularity Correspondence Learning from Long-term Noisy Videos Yijie Lin, Jie Zhang, Zhenyu Huang, Jia Liu, zujie wen, Xi Peng

PAC Prediction Sets Under Label Shift Wenwen Si, Sangdon Park, Insup Lee, Edgar Dobriban, Osbert Bastani

BTR: Binary Token Representations for Efficient Retrieval Augmented Language Models Qingqing Cao, Sewon Min, Yizhong Wang, Hannaneh Hajishirzi

Treatment Effects Estimation By Uniform Transformer Ruoqi Yu, Shulei Wang

Deep Temporal Graph Clustering Meng Liu, Yue Liu, KE LIANG, Wenxuan Tu, Siwei Wang, sihang zhou, Xinwang Liu

Active Test-Time Adaptation: Theoretical Analyses and An Algorithm Shurui Gui, Xiner Li, Shuiwang Ji

Learning to Reject with a Fixed Predictor: Application to Decontextualization Christopher Mohri, Daniel Andor, Eunsol Choi, Michael Collins, Anqi Mao, Yutao Zhong

Pre-Training Goal-based Models for Sample-Efficient Reinforcement Learning Haoqi Yuan, Zhancun Mu, Feiyang Xie, Zongqing Lu

LLaMA-Adapter: Efficient Fine-tuning of Large Language Models with Zero-initialized Attention Renrui Zhang, Jiaming Han, Chris Liu, Aojun Zhou, Pan Lu, Yu Qiao, Hongsheng Li, Gao Peng

Bidirectional Temporal Diffusion Model for Temporally Consistent Human Animation Tserendorj Adiya, Jae Shin Yoon, Jung Eun Lee, Sanghun Kim, Hwasup Lim

Zipformer: A faster and better encoder for automatic speech recognition Zengwei Yao, Liyong Guo, Xiaoyu Yang, Wei Kang, Fangjun Kuang, Yifan Yang, Zengrui Jin, Long Lin, Daniel Povey

Does Progress On Object Recognition Benchmarks Improve Generalization on Crowdsourced, Global Data? Megan Richards, Polina Kirichenko, Diane Bouchacourt, Mark Ibrahim

Differentiable Euler Characteristic Transforms for Shape Classification Ernst Roell, Bastian Rieck

Consistency Trajectory Models: Learning Probability Flow ODE Trajectory of Diffusion Dongjun Kim, Chieh-Hsin Lai, WeiHsiang Liao, Naoki Murata, Yuhta Takida, Toshimitsu Uesaka, Yutong He, Yuki Mitsufuji, Stefano Ermon

FedInverse: Evaluating Privacy Leakage in Federated Learning DI WU, Jun Bai, Yiliao Song, Junjun Chen, Wei Zhou, Yong Xiang, Atul Sajjanhar

Variance-enlarged Poisson Learning for Graph-based Semi-Supervised Learning with Extremely Sparse Labeled Data Xiong Zhou, Xianming Liu, Hao Yu, Jialiang Wang, Zeke Xie, Junjun Jiang, Xiangyang Ji

An Extensible Framework for Open Heterogeneous Collaborative Perception Yifan Lu, Yue Hu, Yiqi Zhong, Dequan Wang, Yanfeng Wang, Siheng Chen

KoLA: Carefully Benchmarking World Knowledge of Large Language Models Jifan Yu, Xiaozhi Wang, Shangqing Tu, Shulin Cao, Daniel Zhang-Li, Xin Lv, Hao Peng, Zijun Yao, Xiaohan Zhang, Hanming Li, Chunyang Li, Zheyuan Zhang, Yushi Bai, Yantao Liu, Amy Xin, Kaifeng Yun, Linlu Gong, Nianyi Lin, Jianhui Chen, Zhili Wu, Yunjia Qi, Weikai Li, Yong Guan, Kaisheng Zeng, Ji Qi, Hailong Jin, Jinxin Liu, Yu Gu, Yuan Yao, Ning Ding, Lei Hou, Zhiyuan Liu, Xu Bin, Jie Tang, Juanzi Li

Yet Another ICU Benchmark: A Flexible Multi-Center Framework for Clinical ML Robin van de Water, Hendrik Schmidt, Paul Elbers, Patrick Thoral, Bert Arnrich, Patrick Rockenschaub

When Scaling Meets LLM Finetuning: The Effect of Data, Model and Finetuning Method Biao Zhang, Zhongtao Liu, Colin Cherry, Orhan Firat

Improving Generalization of Alignment with Human Preferences through Group Invariant Learning Rui Zheng, Wei Shen, Yuan Hua, Wenbin Lai, Shihan Dou, Yuhao Zhou, Zhiheng Xi, Xiao Wang, Haoran Huang, Tao Gui, Qi Zhang, Xuanjing Huang

Efficient Sharpness-Aware Minimization for Molecular Graph Transformer Models Yili Wang, Kaixiong Zhou, Ninghao Liu, Ying Wang, Xin Wang

Latent Trajectory Learning for Limited Timestamps under Distribution Shift over Time Qiuhao Zeng, Changjian Shui, Long-Kai Huang, Peng Liu, Xi Chen, Charles Ling, Boyu Wang

MovingParts: Motion-based 3D Part Discovery in Dynamic Radiance Field Kaizhi Yang, Xiaoshuai Zhang, Zhiao Huang, Xuejin Chen, Zexiang Xu, Hao Su

Efficient-3Dim: Learning a Generalizable Single-image Novel-view Synthesizer in One Day Yifan Jiang, Hao Tang, Jen-Hao Chang, Liangchen Song, Zhangyang Wang, Liangliang Cao

Manifold Preserving Guided Diffusion Yutong He, Naoki Murata, Chieh-Hsin Lai, Yuhta Takida, Toshimitsu Uesaka, Dongjun Kim, WeiHsiang Liao, Yuki Mitsufuji, Zico Kolter, Ruslan Salakhutdinov, Stefano Ermon

Fine-Tuning Language Models for Factuality Katherine Tian, Eric Mitchell, Huaxiu Yao, Christopher Manning, Chelsea Finn

Dual Associated Encoder for Face Restoration Yu-Ju Tsai, Yu-Lun Liu, Lu Qi, Kelvin Chan, Ming-Hsuan Yang

Unmasking and Improving Data Credibility: A Study with Datasets for Training Harmless Language Models Zhaowei Zhu, Jialu Wang, Hao Cheng, Yang Liu

RT-Trajectory: Robotic Task Generalization via Hindsight Trajectory Sketches Jiayuan Gu, Sean Kirmani, Paul Wohlhart, Yao Lu, Montserrat Gonzalez Arenas, Kanishka Rao, Wenhao Yu, Chuyuan Fu, Keerthana Gopalakrishnan, Zhuo Xu, Priya Sundaresan, Peng Xu, Hao Su, Karol Hausman, Chelsea Finn, Quan Vuong, Ted Xiao

Generating Images with 3D Annotations Using Diffusion Models Wufei Ma, Qihao Liu, Jiahao Wang, Angtian Wang, Xiaoding Yuan, Yi Zhang, Zihao Xiao, Guofeng Zhang, Beijia Lu, Ruxiao Duan, Yongrui Qi, Adam Kortylewski, Yaoyao Liu, Alan Yuille

Knowledge Distillation Based on Transformed Teacher Matching Kaixiang Zheng, EN-HUI YANG

Less is More: One-shot Subgraph Reasoning on Large-scale Knowledge Graphs (Andrew) Zhanke Zhou, Yongqi Zhang, Jiangchao Yao, Quanming Yao, Bo Han

Ground-A-Video: Zero-shot Grounded Video Editing using Text-to-image Diffusion Models Hyeonho Jeong, Jong Chul YE

MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models Longhui Yu, Weisen JIANG, Han Shi, Jincheng YU, Zhengying Liu, Yu Zhang, James Kwok, Zhenguo Li, Adrian Weller, Weiyang Liu

Pre-Training and Fine-Tuning Generative Flow Networks Ling Pan, Moksh Jain, Kanika Madan, Yoshua Bengio

Crystalformer: Infinitely Connected Attention for Periodic Structure Encoding Tatsunori Taniai, Ryo Igarashi, Yuta Suzuki, Naoya Chiba, Kotaro Saito, Yoshitaka Ushiku, Kanta Ono

ExeDec: Execution Decomposition for Compositional Generalization in Neural Program Synthesis Kensen Shi, Joey Hong, Yinlin Deng, Pengcheng Yin, Manzil Zaheer, Charles Sutton

On the Humanity of Conversational AI: Evaluating the Psychological Portrayal of LLMs Jen-Tse Huang, Wenxuan Wang, Eric John Li, Man Ho LAM, Shujie Ren, Youliang Yuan, Wenxiang Jiao, Zhaopeng Tu, Michael Lyu

Memory-Consistent Neural Networks for Imitation Learning Kaustubh Sridhar, Souradeep Dutta, Dinesh Jayaraman, James Weimer, Insup Lee

Light-MILPopt: Solving Large-scale Mixed Integer Linear Programs with Lightweight Optimizer and Small-scale Training Dataset Huigen Ye, Hua Xu, Hongyan Wang

Learning Interactive Real-World Simulators Sherry Yang, Yilun Du, Seyed Ghasemipour, Jonathan Tompson, Leslie Kaelbling, Dale Schuurmans, Pieter Abbeel

Dissecting learning and forgetting in language model finetuning Xiao Zhang, Ji Wu

Learning to Reject Meets Long-tail Learning Harikrishna Narasimhan, Aditya Krishna Menon, Wittawat Jitkrittum, Neha Gupta, Sanjiv Kumar

Fusing Models with Complementary Expertise Hongyi Wang, Felipe Maia Polo, Yuekai Sun, Souvik Kundu, Eric Xing, Mikhail Yurochkin

AirPhyNet: Harnessing Physics-Guided Neural Networks for Air Quality Prediction Kethmi Hirushini Hettige, Jiahao Ji, Shili Xiang, Cheng Long, Gao Cong, Jingyuan Wang

FeatUp: A Model-Agnostic Framework for Features at Any Resolution Stephanie Fu, Mark Hamilton, Laura E. Brandt, Axel Feldmann, Zhoutong Zhang, William Freeman

P2Seg: Pointly-supervised Segmentation via Mutual Distillation Zipeng Wang, Xuehui Yu, Xumeng Han, Wenwen Yu, Zhixun Huang, Jianbin Jiao, Zhenjun Han

Graph Neural Networks for Learning Equivariant Representations of Neural Networks Miltiadis (Miltos) Kofinas, Boris Knyazev, Yan Zhang, Yunlu Chen, Gertjan J Burghouts, Efstratios Gavves, Cees G Snoek, David Zhang

Time Fairness in Online Knapsack Problems Adam Lechowicz, Rik Sengupta, Bo Sun, Shahin Kamali, Mohammad Hajiesmaili

Unbiased Watermark for Large Language Models Zhengmian Hu, Lichang Chen, Xidong Wu, Yihan Wu, Hongyang Zhang, Heng Huang

Large Content And Behavior Models To Understand, Simulate, And Optimize Content And Behavior Ashmit Khandelwal, Aditya Agrawal, Aanisha Bhattacharyya, Yaman Singla, Somesh Singh, Uttaran Bhattacharya, Ishita Dasgupta, Stefano Petrangeli, Rajiv Ratn Shah, Changyou Chen, Balaji Krishnamurthy

NeurRev: Train Better Sparse Neural Network Practically via Neuron Revitalization Gen Li, Lu Yin, Jie Ji, Wei Niu, Minghai Qin, Bin Ren, Linke Guo, Shiwei Liu, Xiaolong Ma

OmniQuant: Omnidirectionally Calibrated Quantization for Large Language Models Wenqi Shao, Mengzhao Chen, Zhaoyang Zhang, Peng Xu, Lirui Zhao, Zhiqian Li, Kaipeng Zhang, Gao Peng, Yu Qiao, Ping Luo

Can Sensitive Information Be Deleted From LLMs? Objectives for Defending Against Extraction Attacks Vaidehi Ramesh Patil, Peter Hase, Mohit Bansal

Langevin Monte Carlo for strongly log-concave distributions: Randomized midpoint revisited LU YU, Avetik Karagulyan, Arnak Dalalyan

New Insight of Variance reduce in Zero-Order Hard-Thresholding: Mitigating Gradient Error and Expansivity Contradictions Xinzhe Yuan, William de Vazelhes, Bin Gu, Huan Xiong

3D-Aware Hypothesis & Verification for Generalizable Relative Object Pose Estimation Chen Zhao, Tong Zhang, Mathieu Salzmann

Query-Policy Misalignment in Preference-Based Reinforcement Learning Xiao Hu, Jianxiong Li, Xianyuan Zhan, Qing-Shan Jia, Ya-Qin Zhang

TopoMLP: A Simple yet Strong Pipeline for Driving Topology Reasoning Dongming Wu, Jiahao Chang, Fan Jia, Yingfei Liu, Tiancai Wang, Jianbing Shen

Finite-State Autoregressive Entropy Coding for Efficient Learned Lossless Compression Yufeng Zhang, Hang Yu, Jianguo Li, Weiyao Lin

Enhancing Group Fairness in Online Settings Using Oblique Decision Forests Somnath Basu Roy Chowdhury, Nicholas Monath, Ahmad Beirami, Rahul Kidambi, Kumar Dubey, Amr Ahmed, Snigdha Chaturvedi

Real3D-Portrait: One-shot Realistic 3D Talking Portrait Synthesis Zhenhui Ye, Tianyun Zhong, Yi Ren, Jiaqi Yang, Weichuang Li, Jiawei Huang, Ziyue Jiang, Jinzheng He, Rongjie Huang, Jinglin Liu, Chen Zhang, Xiang Yin, Zejun MA, Zhou Zhao

Deep Reinforcement Learning Guided Improvement Heuristic for Job Shop Scheduling Cong Zhang, Zhiguang Cao, Wen Song, Yaoxin Wu, Jie Zhang

Unleashing the Power of Pre-trained Language Models for Offline Reinforcement Learning Ruizhe Shi, Yuyao Liu, Yanjie Ze, Simon Du, Huazhe Xu

Towards Characterizing Domain Counterfactuals for Invertible Latent Causal Models Zeyu Zhou, Ruqi Bai, Sean Kulinski, Murat Kocaoglu, David Inouye

Interventional Fairness on Partially Known Causal Graphs: A Constrained Optimization Approach Aoqi Zuo, yiqing li, Susan Wei, Mingming Gong

Idempotence and Perceptual Image Compression Tongda Xu, Ziran Zhu, Dailan He, Yanghao Li, Lina Guo, Yuanyuan Wang, Zhe Wang, Hongwei Qin, Yan Wang, Jingjing Liu, Ya-Qin Zhang

Noise Map Guidance: Inversion with Spatial Context for Real Image Editing Hansam Cho, Jonghyun Lee, Seoung Bum Kim, Tae-Hyun Oh, Yonghyun Jeong

Benign Oscillation of Stochastic Gradient Descent with Large Learning Rate Miao Lu, Beining Wu, Xiaodong Yang, Difan Zou

Unknown Domain Inconsistency Minimization for Domain Generalization Seungjae Shin, HeeSun Bae, Byeonghu Na, Yoon-Yeong, Il-chul Moon

Pre-training Sequence, Structure, and Surface Features for Comprehensive Protein Representation Learning Youhan Lee, Hasun Yu, Jaemyung Lee, Jaehoon Kim

Game-Theoretic Robust Reinforcement Learning Handles Temporally-Coupled Perturbations Yongyuan Liang, Yanchao Sun, Ruijie Zheng, Xiangyu Liu, Benjamin Eysenbach, Tuomas Sandholm, Furong Huang, Stephen McAleer

Training-free Multi-objective Diffusion Model for 3D Molecule Generation XU HAN, Caihua Shan, Yifei Shen, Can Xu, Han Yang, Xiang Li, Dongsheng Li

How Do Transformers Learn In-Context Beyond Simple Functions? A Case Study on Learning with Representations Tianyu Guo, Wei Hu, Song Mei, Huan Wang, Caiming Xiong, Silvio Savarese, Yu Bai

Latent Intuitive Physics: Learning to Transfer Hidden Physics from A 3D Video Xiangming Zhu, Huayu Deng, Haochen Yuan, Yunbo Wang, Xiaokang Yang

Enhancing Transfer Learning with Flexible Nonparametric Posterior Sampling Hyungi Lee, Giung Nam, Edwin Fong, Juho Lee

On the Joint Interaction of Models, Data, and Features Yiding Jiang, Christina Baek, Zico Kolter

CORN: Contact-based Object Representation for Nonprehensile Manipulation of General Unseen Objects Yoonyoung Cho, Junhyek Han, Yoontae Cho, Beomjoon Kim

Modelling complex vector drawings with stroke-clouds Alexander Ashcroft, Ayan Das, Yulia Gryaditskaya, Zhiyu Qu, Yi-Zhe Song

Protein Multimer Structure Prediction via Prompt Learning Ziqi Gao, Xiangguo SUN, Zijing Liu, Yu Li, Hong Cheng, Jia Li

Improved statistical and computational complexity of the mean-field Langevin dynamics under structured data Atsushi Nitanda, Kazusato Oko, Taiji Suzuki, Denny Wu

Epitopological learning and Cannistraci-Hebb network shape intelligence brain-inspired theory for ultra-sparse advantage in deep learning Yingtao Zhang, Jialin Zhao, Wenjing Wu, Alessandro Muscoloni, Carlo Vittorio Cannistraci

SAS: Structured Activation Sparsification Yusuke Sekikawa, Shingo Yashima

Certified Adversarial Robustness for Rate Encoded Spiking Neural Networks Bhaskar Mukhoty, Hilal AlQuabeh, Giulia De Masi, Huan Xiong, Bin Gu

Kernelised Normalising Flows Eshant English, Matthias Kirchler, Christoph Lippert

Sample-efficient Learning of Infinite-horizon Average-reward MDPs with General Function Approximation Jianliang He, Han Zhong, Zhuoran Yang

Spectrally Transformed Kernel Regression Runtian Zhai, Rattana Pukdee, Roger Jin, Nina Balcan, Pradeep K Ravikumar

MIntRec2.0: A Large-scale Benchmark Dataset for Multimodal Intent Recognition and Out-of-scope Detection in Conversations Hanlei Zhang, Xin Wang, Hua Xu, Qianrui Zhou, Kai Gao, Jianhua Su, jinyue Zhao, Wenrui Li, Yanting Chen

Out-of-Distribution Detection with Negative Prompts Jun Nie, Yonggang Zhang, Zhen Fang, Tongliang Liu, Bo Han, Xinmei Tian

Manipulating dropout reveals an optimal balance of efficiency and robustness in biological and machine visual systems Jacob Prince, Gabriel Fajardo, George Alvarez, Talia Konkle

Open-ended VQA benchmarking of Vision-Language models by exploiting Classification datasets and their semantic hierarchy Simon Ging, Maria A. Bravo, Thomas Brox

Local Composite Saddle Point Optimization Cedar Site Bai, Brian Bullins

VCR-Graphormer: A Mini-batch Graph Transformer via Virtual Connections Dongqi Fu, Zhigang Hua, Yan Xie, Jin Fang, Si Zhang, Kaan Sancak, Hao Wu, Andrey Malevich, Jingrui He, Bo Long

Adaptive Sharpness-Aware Pruning for Robust Sparse Networks Anna Bair, Hongxu Yin, Maying Shen, Pavlo Molchanov, Jose M. Alvarez

Generalization in diffusion models arises from geometry-adaptive harmonic representations Zahra Kadkhodaie, Florentin Guth, Eero Simoncelli, Stéphane Mallat

Improving protein optimization with smoothed fitness landscapes Andrew Kirjner, Jason Yim, Raman Samusevich, Shahar Bracha, Tommi Jaakkola, Regina Barzilay, Ila Fiete

FedP3: Federated Personalized and Privacy-friendly Network Pruning under Model Heterogeneity Kai Yi, Nidham Gazagnadou, Peter Richtarik, Lingjuan Lyu

PORF: POSE RESIDUAL FIELD FOR ACCURATE NEURAL SURFACE RECONSTRUCTION Jia-Wang Bian, Wenjing Bian, Victor Prisacariu, Philip Torr

Adaptive Instrument Design for Indirect Experiments Yash Chandak, Shiv Shankar, Vasilis Syrgkanis, Emma Brunskill

ImagenHub: Standardizing the evaluation of conditional image generation models Max Ku, Tianle Li, Kai Zhang, Yujie Lu, XINGYU FU, Wenwen Zhuang, Wenhu Chen

Provably Efficient UCB-type Algorithms For Learning Predictive State Representations Ruiquan Huang, Yingbin Liang, Jing Yang

Uni3D: Exploring Unified 3D Representation at Scale Junsheng Zhou, Jinsheng Wang, Baorui Ma, Yu-Shen Liu, Tiejun Huang, Xinlong Wang

ReTaSA: A Nonparametric Functional Estimation Approach for Addressing Continuous Target Shift Hwanwoo Kim, Xin Zhang, Jiwei Zhao, Qinglong Tian

CrIBo: Self-Supervised Learning via Cross-Image Object-Level Bootstrapping Tim Lebailly, Thomas Stegmüller, Behzad Bozorgtabar, Jean-Philippe Thiran, Tinne Tuytelaars

Soft Contrastive Learning for Time Series Seunghan Lee, Taeyoung Park, Kibok Lee

Data Debugging with Shapley Importance over Machine Learning Pipelines Bojan Karlaš, David Dao, Matteo Interlandi, Sebastian Schelter, Wentao Wu, Ce Zhang

Neural Field Classifiers via Target Encoding and Classification Loss Xindi Yang, Zeke Xie, Xiong Zhou, Boyu Liu, Buhua Liu, Yi Liu, Haoran Wang, YUNFENG CAI, Mingming Sun

CrossLoco: Human Motion Driven Control of Legged Robots via Guided Unsupervised Reinforcement Learning Tianyu Li, Hyunyoung Jung, Matthew Gombolay, Yong Cho, Sehoon Ha

Parametric Augmentation for Time Series Contrastive Learning Xu Zheng, Tianchun Wang, Wei Cheng, Aitian Ma, Haifeng Chen, Mo Sha, Dongsheng Luo

Patched Denoising Diffusion Models For High-Resolution Image Synthesis Zheng Ding, Mengqi Zhang, Jiajun Wu, Zhuowen Tu

Reverse Forward Curriculum Learning for Extreme Sample and Demo Efficiency Stone Tao, Arth Shukla, Tse-kai Chan, Hao Su

Entropy is not Enough for Test-Time Adaptation: From the Perspective of Disentangled Factors Jonghyun Lee, Dahuin Jung, Saehyung Lee, Junsung Park, Juhyeon Shin, Uiwon Hwang, Sungroh Yoon

A Study of Bayesian Neural Network Surrogates for Bayesian Optimization Yucen Li, Tim G. J. Rudner, Andrew Gordon Wilson

Towards Optimal Regret in Adversarial Linear MDPs with Bandit Feedback Haolin Liu, Chen-Yu Wei, Julian Zimmert

GoLLIE: Annotation Guidelines improve Zero-Shot Information-Extraction Oscar Sainz, Iker García-Ferrero, Rodrigo Agerri, Oier Lacalle, German Rigau, Eneko Agirre

Performance Gaps in Multi-view Clustering under the Nested Matrix-Tensor Model Hugo Lebeau, Mohamed El Amine Seddik, José Henrique Goulart

VQ-TR: Vector Quantized Attention for Time Series Forecasting Kashif Rasul, Andrew Bennett, Pablo Vicente, Umang Gupta, Hena Ghonia, Anderson Schneider, Yuriy Nevmyvaka

The Generative AI Paradox: “What It Can Create, It May Not Understand” Peter West, Ximing Lu, Nouha Dziri, Faeze Brahman, Linjie Li, Jena Hwang, Liwei Jiang, Jillian Fisher, Abhilasha Ravichander, Khyathi Chandu, Benjamin Newman, Pang Wei Koh, Allyson Ettinger, Yejin Choi

Increasing Model Capacity for Free: A Simple Strategy for Parameter Efficient Fine-tuning Haobo Song, Hao Zhao, Soumajit Majumder, Tao Lin

Diffusion Generative Flow Samplers: Improving learning signals through partial trajectory optimization Dinghuai Zhang, Ricky T. Q. Chen, Chenghao Liu, Aaron Courville, Yoshua Bengio

Doubly Robust Proximal Causal Learning for Continuous Treatments Yong Wu, Yanwei Fu, Shouyan Wang, Xinwei Sun

Learning Performance-Improving Code Edits Alexander Shypula, Aman Madaan, Yimeng Zeng, Uri Alon, Jacob Gardner, Yiming Yang, Milad Hashemi, Graham Neubig, Parthasarathy Ranganathan, Osbert Bastani, Amir Yazdanbakhsh

Mixture of LoRA Experts xun wu, Shaohan Huang, Furu Wei

Scalable Diffusion for Materials Generation Sherry Yang, Kwanghwan Cho, Amil Merchant, Pieter Abbeel, Dale Schuurmans, Igor Mordatch, Ekin Cubuk

In-context Exploration-Exploitation for Reinforcement Learning Zhenwen Dai, Federico Tomasi, Sina Ghiassian

Federated Orthogonal Training: Mitigating Global Catastrophic Forgetting in Continual Federated Learning Yavuz Faruk Bakman, Duygu Nur Yaldiz, Yahya Ezzeldin, Salman Avestimehr

TD-MPC2: Scalable, Robust World Models for Continuous Control Nick Hansen, Hao Su, Xiaolong Wang

Bayesian Optimization through Gaussian Cox Process Models for Spatio-temporal Data Yongsheng Mei, Mahdi Imani, Tian Lan

CODE REPRESENTATION LEARNING AT SCALE Dejiao Zhang, Wasi Ahmad, Ming Tan, Hantian Ding, Ramesh Nallapati, Dan Roth, Xiaofei Ma, Bing Xiang

Diverse Projection Ensembles for Distributional Reinforcement Learning Moritz Akiya Zanger, Wendelin Boehmer, Matthijs T. J. Spaan

On Penalty Methods for Nonconvex Bilevel Optimization and First-Order Stochastic Approximation Jeongyeol Kwon, Dohyun Kwon, Stephen Wright, Robert Nowak

R-MAE: Regions Meet Masked Autoencoders Duy-Kien Nguyen, Yanghao Li, Vaibhav Aggarwal, Martin R. Oswald, Alexander Kirillov, Cees G Snoek, Xinlei Chen

The Wasserstein Believer: Learning Belief Updates for Partially Observable Environments through Reliable Latent Space Models Raphael Avalos, Florent Delgrange, Ann Nowe, Guillermo Perez, Diederik M. Roijers

Contrastive Difference Predictive Coding Chongyi Zheng, Ruslan Salakhutdinov, Benjamin Eysenbach

Provable and Practical: Efficient Exploration in Reinforcement Learning via Langevin Monte Carlo Haque Ishfaq, Qingfeng Lan, Pan Xu, A. Rupam Mahmood, Doina Precup, anima anandkumar, Kamyar Azizzadenesheli

Decoding Natural Images from EEG for Object Recognition Yonghao Song, Bingchuan Liu, Xiang Li, Nanlin Shi, Yijun Wang, Xiaorong Gao

DRSM: De-Randomized Smoothing on Malware Classifier Providing Certified Robustness Shoumik Saha, Wenxiao Wang, Yigitcan Kaya, Soheil Feizi, Tudor Dumitras

Fully Hyperbolic Convolutional Neural Networks for Computer Vision Ahmad Bdeir, Kristian Schwethelm, Niels Landwehr

GTMGC: Using Graph Transformer to Predict Molecule’s Ground-State Conformation Guikun Xu, Yongquan Jiang, PengChuan Lei, Yan Yang, Jim Chen

High-dimensional SGD aligns with emerging outlier eigenspaces Gerard Ben Arous, Reza Gheissari, Jiaoyang Huang, Aukosh Jagannath

Balancing Act: Constraining Disparate Impact in Sparse Models Meraj Hashemizadeh, Juan Ramirez, Rohan Sukumaran, Golnoosh Farnadi, Simon Lacoste-Julien, Jose Gallego-Posada

Demystifying CLIP Data Hu Xu, Saining Xie, Xiaoqing Tan, Po-Yao Huang, Russell Howes, Vasu Sharma, Shang-Wen Li, Gargi Ghosh, Luke Zettlemoyer, Christoph Feichtenhofer

RepoBench: Benchmarking Repository-Level Code Auto-Completion Systems Tianyang Liu, Canwen Xu, Julian McAuley

Unified Generative Modeling of 3D Molecules with Bayesian Flow Networks Yuxuan Song, Jingjing Gong, Hao Zhou, Mingyue Zheng, Jingjing Liu, Wei-Ying Ma

InsertNeRF: Instilling Generalizability into NeRF with HyperNet Modules Yanqi Bao, Tianyu Ding, Jing Huo, Wenbin Li, Yuxin Li, Yang Gao

Universal Jailbreak Backdoors from Poisoned Human Feedback Javier Rando, Florian Tramer

Flow Matching on General Geometries Ricky T. Q. Chen, Yaron Lipman

Neural Processing of Tri-Plane Hybrid Neural Fields Adriano Cardace, Pierluigi Zama Ramirez, Francesco Ballerini, Allan Zhou, Samuele Salti, Luigi Di Stefano

SpaCE: The Spatial Confounding Environment Mauricio Tec, Ana Trisovic, Michelle Audirac, Sophie Woodward, Jie Hu, Naeem Khoshnevis, Francesca Dominici

On Adversarial Training without Perturbing all Examples Max Losch, Mohamed Omran, David Stutz, Mario Fritz, Bernt Schiele

Network Memory Footprint Compression Through Jointly Learnable Codebooks and Mappings Edouard YVINEC, Arnaud Dapogny, Kevin Bailly

A Unified Sampling Framework for Solver Searching of Diffusion Probabilistic Models Enshu Liu, Xuefei Ning, Huazhong Yang, Yu Wang

Periodicity Decoupling Framework for Long-term Series Forecasting Tao Dai, Beiliang Wu, Peiyuan Liu, Naiqi Li, Jigang Bao, Yong Jiang, Shu-Tao Xia

EQA-MX: Embodied Question Answering using Multimodal Expression Md Mofijul Islam, Alexi Gladstone, Riashat Islam, Tariq Iqbal

Evaluating the Zero-shot Robustness of Instruction-tuned Language Models Jiuding Sun, Chantal Shaib, Byron Wallace

Magic123: One Image to High-Quality 3D Object Generation Using Both 2D and 3D Diffusion Priors Guocheng Qian, Jinjie Mai, Abdullah Hamdi, Jian Ren, Aliaksandr Siarohin, Bing Li, Hsin-Ying Lee, Ivan Skorokhodov, Peter Wonka, Sergey Tulyakov, Bernard Ghanem

Scaling Laws of RoPE-based Extrapolation Xiaoran Liu, Hang Yan, Chenxin An, Xipeng Qiu, Dahua Lin

Enhancing Neural Training via a Correlated Dynamics Model Jonathan Brokman, Roy Betser, Rotem Turjeman, Tom Berkov, Ido Cohen, Guy Gilboa

Mol-Instructions: A Large-Scale Biomolecular Instruction Dataset for Large Language Models Yin Fang, Xiaozhuan Liang, Ningyu Zhang, Kangwei Liu, Rui Huang, Zhuo Chen, Xiaohui Fan, Huajun Chen

Reasoning with Latent Diffusion in Offline Reinforcement Learning Siddarth Venkatraman, Shivesh Khaitan, Ravi Tej Akella, John Dolan, Jeff Schneider, Glen Berseth

Sampling Multimodal Distributions with the Vanilla Score: Benefits of Data-Based Initialization Frederic Koehler, Thuy-Duong Vuong

Conversational Drug Editing Using Retrieval and Domain Feedback Shengchao Liu, Jiongxiao Wang, Yijin Yang, Chengpeng Wang, Ling Liu, Hongyu Guo, Chaowei Xiao

ToRA: A Tool-Integrated Reasoning Agent for Mathematical Problem Solving Zhibin Gou, Zhihong Shao, Yeyun Gong, yelong shen, Yujiu Yang, Minlie Huang, Nan Duan, Weizhu Chen

ViDA: Homeostatic Visual Domain Adapter for Continual Test Time Adaptation Jiaming Liu, Senqiao Yang, Peidong Jia, Renrui Zhang, Ming Lu, Yandong Guo, Wei Xue, Shanghang Zhang

Efficient local linearity regularization to overcome catastrophic overfitting Elias Abad Rocamora, Fanghui Liu, Grigorios Chrysos, Pablo M. Olmos, Volkan Cevher

Discovering Failure Modes of Text-guided Diffusion Models via Adversarial Search Qihao Liu, Adam Kortylewski, Yutong Bai, Song Bai, Alan Yuille

Neural Neighborhood Search for Multi-agent Path Finding Zhongxia Yan, Cathy Wu

Forward Learning with Top-Down Feedback: Empirical and Analytical Characterization Ravi Srinivasan, Francesca Mignacco, Martino Sorbaro, Maria Refinetti, Avi Cooper, Gabriel Kreiman, Giorgia Dellaferrera

Chain-of-Experts: When LLMs Meet Complex Operations Research Problems Ziyang Xiao, Dongxiang Zhang, Yangjun Wu, Lilin Xu, Yuan Wang, Xiongwei Han, Xiaojin Fu, Tao Zhong, Jia Zeng, Mingli Song, Gang Chen

Adversarial Attacks on Fairness of Graph Neural Networks Binchi Zhang, Yushun Dong, Chen Chen, Yada Zhu, Minnan Luo, Jundong Li

DNA-GPT: Divergent N-Gram Analysis for Training-Free Detection of GPT-Generated Text Xianjun Yang, Wei Cheng, Yue Wu, Linda Petzold, William Wang, Haifeng Chen

Benchmarking Algorithms for Federated Domain Generalization Ruqi Bai, Saurabh Bagchi, David Inouye

Adapting Large Language Models via Reading Comprehension Daixuan Cheng, Shaohan Huang, Furu Wei

Rigid Protein-Protein Docking via Equivariant Elliptic-Paraboloid Interface Prediction Ziyang Yu, Wenbing Huang, Yang Liu

Tree-Planner: Efficient Close-loop Task Planning with Large Language Models Mengkang Hu, Yao Mu, Xinmiao Yu, Mingyu Ding, Shiguang Wu, Wenqi Shao, Qiguang Chen, Bin Wang, Yu Qiao, Ping Luo

Data Distillation Can Be Like Vodka: Distilling More Times For Better Quality Xuxi Chen, Yu Yang, Zhangyang Wang, Baharan Mirzasoleiman

On gauge freedom, conservativity and intrinsic dimensionality estimation in diffusion models Christian Horvat, Jean-Pascal Pfister

Jointly Training Large Autoregressive Multimodal Models Emanuele Aiello, Lili Yu, Yixin Nie, Armen Aghajanyan, Barlas Oguz

Win-Win: Training High-Resolution Vision Transformers from Two Windows Vincent Leroy, Jerome Revaud, Thomas Lucas, Philippe Weinzaepfel

Self-Supervised Heterogeneous Graph Learning: a Homophily and Heterogeneity View YUJIE MO, Feiping Nie, Ping Hu, Heng Tao Shen, Zheng Zhang, Xinchao Wang, Xiaofeng Zhu

Large Language Models as Automated Aligners for benchmarking Vision-Language Models Yuanfeng Ji, Chongjian GE, Weikai Kong, Enze Xie, Zhengying Liu, Zhenguo Li, Ping Luo

Debiased Collaborative Filtering with Kernel-Based Causal Balancing Haoxuan Li, Chunyuan Zheng, Yanghao Xiao, Peng Wu, Zhi Geng, Xu Chen, Peng Cui

Language Model Self-improvement by Reinforcement Learning Contemplation Jing-Cheng Pang, Pengyuan Wang, Kaiyuan Li, XiongHui Chen, Jiacheng Xu, Zongzhang Zhang, Yang Yu

Zero Bubble (Almost) Pipeline Parallelism Penghui Qi, Xinyi Wan, Guangxing Huang, Min Lin

Unraveling the Key Components of OOD Generalization via Diversification Harold Benoit, Liangze Jiang, Andrei Atanov, Oguzhan Kar, Mattia Rigotti, Amir Zamir

Beyond IID weights: sparse and low-rank deep Neural Networks are also Gaussian Processes Thiziri Nait Saada, Alireza Naderi, Jared Tanner

Faithful Explanations of Black-box NLP Models Using LLM-generated Counterfactuals Yair Gat, Nitay Calderon, Amir Feder, Alexander Chapanin, Amit Sharma, Roi Reichart

A Plug-and-Play Image Registration Network JUNHAO HU, Weijie Gan, Zhixin Sun, Hongyu An, Ulugbek Kamilov

Structuring Representation Geometry with Rotationally Equivariant Contrastive Learning Sharut Gupta, Joshua Robinson, Derek Lim, Soledad Villar, Stefanie Jegelka

Solving High Frequency and Multi-Scale PDEs with Gaussian Processes Shikai Fang, Madison Cooley, Da Long, Shibo Li, Mike Kirby, Shandian Zhe

Multi-Resolution Diffusion Models for Time Series Forecasting Lifeng Shen, Weiyu Chen, James Kwok

Principled Federated Domain Adaptation: Gradient Projection and Auto-Weighting Enyi Jiang, Yibo Jacky Zhang, Sanmi Koyejo

Neural Contractive Dynamical Systems Hadi Beik Mohammadi, Søren Hauberg, Georgios Arvanitidis, Nadia Figueroa, Gerhard Neumann, Leonel Rozo

HoloNets: Spectral Convolutions do extend to Directed Graphs Christian Koke, Daniel Cremers

Uni-RLHF: Universal Platform and Benchmark Suite for Reinforcement Learning with Diverse Human Feedback Yifu Yuan, Jianye HAO, Yi Ma, Zibin Dong, Hebin Liang, Jinyi Liu, Zhixin Feng, Kai Zhao, YAN ZHENG

HYPO: Hyperspherical Out-Of-Distribution Generalization Haoyue Bai, Yifei Ming, Julian Katz-Samuels, Yixuan Li

GNNCert: Deterministic Certification of Graph Neural Networks against Adversarial Perturbations Zaishuo Xia, Han Yang, Binghui Wang, Jinyuan Jia

On the Posterior Distribution in Denoising: Application to Uncertainty Quantification Hila Manor, Tomer Michaeli

Jumanji: a Diverse Suite of Scalable Reinforcement Learning Environments in JAX Clem Bonnet, Daniel Luo, Donal Byrne, Shikha Surana, Sasha Abramowitz, Paul Duckworth, Vincent Coyette, Laurence Midgley, Elshadai Tegegn, Tristan Kalloniatis, Omayma Mahjoub, Matthew Macfarlane, Andries Smit, Nathan Grinsztajn, Raphael Boige, Cemlyn Waters, Mohamed Ali Mimouni, Ulrich Mbou Sob, Ruan de Kock, Siddarth Singh, Daniel Furelos-Blanco, Victor Le, Arnu Pretorius, Alexandre Laterre

Remote Sensing Vision-Language Foundation Models without Annotations via Ground Remote Alignment Utkarsh Kumar Mall, Cheng Perng Phoo, Meilin Liu, Carl Vondrick, Bharath Hariharan, Kavita Bala

An Intuitive Multi-Frequency Feature Representation for SO(3)-Equivariant Networks Dongwon Son, Jaehyung Kim, Sanghyeon Son, Beomjoon Kim

DiffEnc: Variational Diffusion with a Learned Encoder Beatrix M. G. Nielsen, Anders Christensen, Andrea Dittadi, Ole Winther

Fast and unified path gradient estimators for normalizing flows Lorenz Vaitl, Ludwig Winkler, Lorenz Richter, Pan Kessel

ReLoRA: High-Rank Training Through Low-Rank Updates Vladislav Lialin, Sherin Muckatira, Namrata Shivagunde, Anna Rumshisky

SparseDFF: Sparse-View Feature Distillation for One-Shot Dexterous Manipulation Qianxu Wang, Haotong Zhang, Congyue Deng, Yang You, Hao Dong, Yixin Zhu, Leonidas Guibas

Bounding the Expected Robustness of Graph Neural Networks Subject to Node Feature Attacks Yassine ABBAHADDOU, Sofiane ENNADIR, Johannes Lutzeyer, Michalis Vazirgiannis, Henrik Boström

Rethinking the Benefits of Steerable Features in 3D Equivariant Graph Neural Networks Shih-Hsin Wang, Yung-Chang Hsu, Justin Baker, Andrea Bertozzi, Jack Xin, Bao Wang

Efficient Multi-agent Reinforcement Learning by Planning Qihan Liu, Jianing Ye, Xiaoteng Ma, Jun Yang, Bin Liang, Chongjie Zhang

Symmetric Single Index Learning Aaron Zweig, Joan Bruna

Time-Efficient Reinforcement Learning with Stochastic Stateful Policies Firas Al-Hafez, Guoping Zhao, Jan Peters, Davide Tateo

Retrieval meets Long Context Large Language Models Peng Xu, Wei Ping, Xianchao Wu, Lawrence McAfee, Chen Zhu, Zihan Liu, Sandeep Subramanian, Evelina Bakhturina, Mohammad Shoeybi, Bryan Catanzaro

Enhancing Contrastive Learning for Ordinal Regression via Ordinal Content Preserved Data Augmentation Jiyang Zheng, Yu Yao, Bo Han, Dadong Wang, Tongliang Liu

Training Socially Aligned Language Models on Simulated Social Interactions Ruibo Liu, Ruixin Yang, Chenyan Jia, Ge Zhang, Diyi Yang, Soroush Vosoughi

Plugin estimators for selective classification with out-of-distribution detection Harikrishna Narasimhan, Aditya Krishna Menon, Wittawat Jitkrittum, Sanjiv Kumar

On the Reliability of Watermarks for Large Language Models John Kirchenbauer, Jonas Geiping, Yuxin Wen, Manli Shu, Khalid Saifullah, Kezhi Kong, Kasun Fernando, Aniruddha Saha, Micah Goldblum, Tom Goldstein

AnomalyCLIP: Object-agnostic Prompt Learning for Zero-shot Anomaly Detection Qihang Zhou, Guansong Pang, Yu Tian, Shibo He, Jiming Chen

Embodied Active Defense: Leveraging Recurrent Feedback to Counter Adversarial Patches Lingxuan Wu, Xiao Yang, Yinpeng Dong, Liuwei XIE, Hang Su, Jun Zhu

Robust Similarity Learning with Difference Alignment Regularization Shuo Chen, Gang Niu, Chen Gong, Okan Koc, Jian Yang, Masashi Sugiyama

In-Context Learning through the Bayesian Prism Madhur Panwar, Kabir Ahuja, Navin Goyal

Small-scale proxies for large-scale Transformer training instabilities Mitchell Wortsman, Peter Liu, Lechao Xiao, Katie Everett, Alexander Alemi, Ben Adlam, JD Co-Reyes, Izzeddin Gur, Abhishek Kumar, Roman Novak, Jeffrey Pennington, Jascha Sohl-Dickstein, Kelvin Xu, Jaehoon Lee, Justin Gilmer, Simon Kornblith

On Trajectory Augmentations for Off-Policy Evaluation Ge Gao, Qitong Gao, Xi Yang, Song Ju, Miroslav Pajic, Min Chi

Adaptive Federated Learning with Auto-Tuned Clients Junhyung Lyle Kim, Mohammad Taha Toghani, Cesar Uribe, Anastasios Kyrillidis

Memorization Capacity of Multi-Head Attention in Transformers Sadegh Mahdavi, Renjie Liao, Christos Thrampoulidis

Understanding In-Context Learning from Repetitions Jianhao (Elliott) Yan, Jin Xu, Chiyu Song, Chenming Wu, Yafu Li, Yue Zhang

COSA: Concatenated Sample Pretrained Vision-Language Foundation Model Sihan Chen, Xingjian He, Handong Li, Xiaojie Jin, Jiashi Feng, Jing Liu

Learning 3D Particle-based Simulators from RGB-D Videos William Whitney, Tatiana Lopez-Guevara, Tobias Pfaff, Yulia Rubanova, Thomas Kipf, Kimberly Stachenfeld, Kelsey Allen

ZeRO++: Extremely Efficient Collective Communication for Large Model Training Guanhua Wang, Heyang Qin, Sam Jacobs, Xiaoxia (Shirley) Wu, Connor Holmes, Zhewei Yao, Samyam Rajbhandari, Olatunji Ruwase, Feng Yan, Lei Yang, Yuxiong He

On the Vulnerability of Adversarially Trained Models Against Two-faced Attacks Shengjie Zhou, Lue Tao, Yuzhou Cao, Tao Xiang, Bo An, Lei Feng

Manifold Diffusion Fields Ahmed Elhag, Yuyang Wang, Joshua Susskind, MIGUEL ANGEL BAUTISTA

HAZARD Challenge: Embodied Decision Making in Dynamically Changing Environments Qinhong Zhou, Sunli Chen, Yisong Wang, Haozhe Xu, Weihua Du, Hongxin Zhang, Yilun Du, Joshua B Tenenbaum, Chuang Gan

Low Rank Matrix Completion via Robust Alternating Minimization in Nearly Linear Time Yuzhou Gu, Zhao Song, Junze Yin, Lichen Zhang

LQ-LoRA: Low-rank plus Quantized Matrix Decomposition for Efficient Language Model Finetuning Han Guo, Philip Greengard, Eric Xing, Yoon Kim

DeepZero: Scaling Up Zeroth-Order Optimization for Deep Model Training AOCHUAN CHEN, Yimeng Zhang, Jinghan Jia, James Diffenderfer, Konstantinos Parasyris, Jiancheng Liu, Yihua Zhang, Zheng Zhang, Bhavya Kailkhura, Sijia Liu

LLM-grounded Video Diffusion Models Long Lian, Baifeng Shi, Adam Yala, trevor darrell, Boyi Li

Transferring Learning Trajectories of Neural Networks Daiki Chijiwa

FairTune: Optimizing Parameter Efficient Fine Tuning for Fairness in Medical Image Analysis Raman Dutt, Ondrej Bohdal, Sotirios Tsaftaris, Timothy Hospedales

CLaM-TTS: Improving Neural Codec Language Model for Zero-Shot Text-to-Speech Jaehyeon Kim, Keon Lee, Seungjun Chung, Jaewoong Cho

Rethinking Branching on Exact Combinatorial Optimization Solver: The First Deep Symbolic Discovery Framework Yufei Kuang, Jie Wang, Haoyang Liu, Fangzhou Zhu, Xijun Li, Jia Zeng, Jianye HAO, Bin Li, Feng Wu

Where We Have Arrived in Proving the Emergence of Sparse Interaction Primitives in DNNs Qihan Ren, Jiayang Gao, Wen Shen, Quanshi Zhang

FedLoGe: Joint Local and Generic Federated Learning under Long-tailed Data Zikai Xiao, Zihan Chen, Liyinglan Liu, YANG FENG, Joey Tianyi Zhou, Jian Wu, Wanlu Liu, Howard Yang, Zuozhu Liu

Deep Confident Steps to New Pockets: Strategies for Docking Generalization Gabriele Corso, Arthur Deng, Nicholas Polizzi, Regina Barzilay, Tommi Jaakkola

Unconstrained Stochastic CCA: Unifying Multiview and Self-Supervised Learning James Chapman, Lennie Wells, Ana Lawry Aguila

Zero-Mean Regularized Spectral Contrastive Learning: Implicitly Mitigating Wrong Connections in Positive-Pair Graphs Xiong Zhou, Xianming Liu, feilong zhang, Gang Wu, Deming Zhai, Junjun Jiang, Xiangyang Ji

Plug-and-Play: An Efficient Post-training Pruning Method for Large Language Models Yingtao Zhang, Haoli Bai, Haokun Lin, Jialin Zhao, LU HOU, Carlo Vittorio Cannistraci

Few-shot Hybrid Domain Adaptation of Image Generator Hengjia Li, Yang Liu, Linxuan Xia, Yuqi Lin, Wenxiao Wang, Tu Zheng, Zheng Yang, Xiaohui Zhong, Xiaobo Ren, Xiaofei He

MT-Ranker: Reference-free machine translation evaluation by inter-system ranking Ibraheem Muhammad Moosa, Rui Zhang, Wenpeng Yin

Generative Modeling of Regular and Irregular Time Series Data via Koopman VAEs Ilan Naiman, N. Benjamin Erichson, Pu Ren, Michael W Mahoney, Omri Azencot

Bayesian Bi-clustering of Neural Spiking Activity with Latent Structures Ganchao Wei

On the Role of General Function Approximation in Offline Reinforcement Learning Chenjie Mao, Qiaosheng Zhang, Zhen Wang, Xuelong Li

Context-Aware Meta-Learning Christopher Fifty, Dennis Duan, Ronald Junkins, Ehsan Amid, Jure Leskovec, Christopher Re, Sebastian Thrun

Channel Vision Transformers: An Image Is Worth 1 x 16 x 16 Words Yujia Bao, Srinivasan Sivanandan, THEOFANIS KARALETSOS

LRM: Large Reconstruction Model for Single Image to 3D Yicong Hong, Kai Zhang, Jiuxiang Gu, Sai Bi, Yang Zhou, Difan Liu, Feng Liu, Kalyan Sunkavalli, Trung Bui, Hao Tan

Optimal Sketching for Residual Error Estimation for Matrix and Vector Norms Yi Li, Honghao Lin, David Woodruff

Learning the greatest common divisor: explaining transformer predictions François Charton

State Representation Learning Using an Unbalanced Atlas Li Meng, Morten Goodwin, Anis Yazidi, Paal Engelstad

Safe RLHF: Safe Reinforcement Learning from Human Feedback Juntao Dai, Xuehai Pan, Ruiyang Sun, Jiaming Ji, Xinbo Xu, Mickel Liu, Yizhou Wang, Yaodong Yang

Accurate Forgetting for Heterogeneous Federated Continual Learning Abudukelimu Wuerkaixi, Sen Cui, Jingfeng Zhang, Kunda Yan, Bo Han, Gang Niu, Lei Fang, Changshui Zhang, Masashi Sugiyama

Symbol as Points: Panoptic Symbol Spotting via Point-based Representation Wenlong Liu, Tianyu Yang, Yuhan Wang, Qizhi Yu, Lei Zhang

Towards Energy Efficient Spiking Neural Networks: An Unstructured Pruning Framework Xinyu Shi, Jianhao Ding, Zecheng Hao, Zhaofei Yu

Object-Aware Inversion and Reassembly for Image Editing Zhen Yang, Ganggui Ding, Wen Wang, Hao Chen, Bohan Zhuang, Chunhua Shen

SALMON: Self-Alignment with Instructable Reward Models Zhiqing Sun, Yikang Shen, Hongxin Zhang, Qinhong Zhou, Zhenfang Chen, David Cox, Yiming Yang, Chuang Gan

Reward Model Ensembles Help Mitigate Overoptimization Thomas Coste, Usman Anwar, Robert Kirk, David Krueger

AffineQuant: Affine Transformation Quantization for Large Language Models Yuexiao Ma, Huixia Li, Xiawu Zheng, Feng Ling, Xuefeng Xiao, Rui Wang, Shilei Wen, Fei Chao, Rongrong Ji

Non-Exchangeable Conformal Risk Control António Farinhas, Chrysoula Zerva, Dennis Ulmer, Andre Martins

Un-Mixing Test-Time Normalization Statistics: Combatting Label Temporal Correlation Devavrat Tomar, Guillaume Vray, Jean-Philippe Thiran, Behzad Bozorgtabar

Class Incremental Learning via Likelihood Ratio Based Task Prediction Haowei Lin, Yijia Shao, Weinan Qian, Ningxin Pan, Yiduo Guo, Bing Liu

Learning Multi-Agent Communication with Contrastive Learning Yat Long (Richie) Lo, Biswa Sengupta, Jakob Foerster, Michael Noukhovitch

AutoVP: An Automated Visual Prompting Framework and Benchmark Hsi-Ai Tsao, Lei Hsiung, Pin-Yu Chen, Sijia Liu, Tsung-Yi Ho

Scale-Adaptive Diffusion Model for Complex Sketch Synthesis Jijin Hu, Ke Li, Yonggang Qi, Yi-Zhe Song

Conditional Information Bottleneck Approach for Time Series Imputation MinGyu Choi, Changhee Lee

One-hot Generalized Linear Model for Switching Brain State Discovery Chengrui Li, Soon Ho Kim, Chris Rodgers, Hannah Choi, Anqi Wu

Effective and Efficient Federated Tree Learning on Hybrid Data Qinbin Li, Chulin Xie, Xiaojun Xu, Xiaoyuan Liu, Ce Zhang, Bo Li, Bingsheng He, Dawn Song

A Poincaré Inequality and Consistency Results for Signal Sampling on Large Graphs Thien Le, Luana Ruiz, Stefanie Jegelka

Faster Approximation of Probabilistic and Distributional Values via Least Squares Weida Li, Yaoliang Yu

Stylized Offline Reinforcement Learning: Extracting Diverse High-Quality Behaviors from Heterogeneous Datasets Yihuan Mao, Chengjie Wu, Xi Chen, Hao Hu, Ji Jiang, Tianze Zhou, Tangjie Lv, Changjie Fan, Zhipeng Hu, Yi Wu, Yujing Hu, Chongjie Zhang

Training Bayesian Neural Networks with Sparse Subspace Variational Inference Junbo Li, Zichen Miao, Qiang Qiu, Ruqi Zhang

Combining Axes Preconditioners through Kronecker Approximation for Deep Learning Venkata Sai Surya Subramanyam Duvvuri, Fnu Devvrit, Rohan Anil, Cho-Jui Hsieh, Inderjit Dhillon

LiDAR-PTQ: Post-Training Quantization for Point Cloud 3D Object Detection Sifan Zhou, Liang Li, Xinyu Zhang, Bo Zhang, Shipeng Bai, Miao Sun, Ziyu Zhao, Xiaobo Lu, Xiangxiang Chu

Structural Fairness-aware Active Learning for Graph Neural Networks Haoyu Han, Xiaorui Liu, Li Ma, MohamadAli Torkamani, Hui Liu, Jiliang Tang, Makoto Yamada

Universal Guidance for Diffusion Models Arpit Bansal, Hong-Min Chu, Avi Schwarzschild, Roni Sengupta, Micah Goldblum, Jonas Geiping, Tom Goldstein

Progressive Fourier Neural Representation for Sequential Video Compilation Haeyong Kang, Jaehong Yoon, DaHyun Kim, Sung Ju Hwang, Chang Yoo

Causally Aligned Curriculum Learning Mingxuan Li, Junzhe Zhang, Elias Bareinboim

Language Control Diffusion: Efficiently Scaling through Space, Time, and Tasks David Bell, Yujie Lu, Shinda Huang, William Wang, Amy Zhang

Principled Architecture-aware Scaling of Hyperparameters Wuyang Chen, Junru Wu, Zhangyang Wang, Boris Hanin

A unique M-pattern for micro-expression spotting in long videos Jinxuan Wang, Shiting Xu, Tong Zhang

Denoising Diffusion via Image-Based Rendering Titas Anciukevičius, Fabian Manhardt, Federico Tombari, Paul Henderson

Masks, Signs, And Learning Rate Rewinding Advait Gadhikar, Rebekka Burkholz

Attention-based Iterative Decomposition for Tensor Product Representation Taewon Park, inchul choi, Minho Lee

A Black-box Approach for Non-stationary Multi-agent Reinforcement Learning Haozhe Jiang, Qiwen Cui, Zhihan Xiong, Maryam Fazel, Simon Du

lpNTK: Better Generalisation with Less Data via Sample Interaction During Learning Shangmin Guo, YI REN, Stefano Albrecht, Kenny Smith

Grounding Multimodal Large Language Models to the World Zhiliang Peng, Wenhui Wang, Li Dong, Yaru Hao, Shaohan Huang, Shuming Ma, Qixiang Ye, Furu Wei

Unified Language-Vision Pretraining in LLM with Dynamic Discrete Visual Tokenization Yang Jin, Kun Xu, Liwei Chen, Chao Liao, Jianchao Tan, Quzhe Huang, Bin CHEN, Chengru Song, dai meng, Di ZHANG, Wenwu Ou, Kun Gai, Yadong MU

Learning Implicit Representation for Reconstructing Articulated Objects Hao Zhang, Fang Li, Samyak Rawlekar, Narendra Ahuja

Amortized Network Intervention to Steer the Excitatory Point Processes Zitao Song, Wendi Ren, Shuang Li

Active Retrosynthetic Planning Aware of Route Quality Luotian Yuan, Yemin Yu, Ying Wei, Yongwei Wang, Zhihua Wang, Fei Wu

Towards Non-Asymptotic Convergence for Diffusion-Based Generative Models Gen Li, Yuting Wei, Yuxin Chen, Yuejie Chi

Enhancing Transferable Adversarial Attacks on Vision Transformers through Gradient Normalization Scaling and High-Frequency Adaptation Zhiyu Zhu, Xinyi Wang, Zhibo Jin, Jiayu Zhang, Huaming Chen

Connect, Collapse, Corrupt: Learning Cross-Modal Tasks with Uni-Modal Data Yuhui Zhang, Elaine Sui, Serena Yeung

Robot Fleet Learning via Policy Merging Lirui Wang, Kaiqing Zhang, Allan Zhou, Max Simchowitz, Russ Tedrake

Finite Scalar Quantization: VQ-VAE Made Simple Fabian Mentzer, David Minnen, Eirikur Agustsson, Michael Tschannen

Object-Centric Learning with Slot Mixture Module Daniil Kirilenko, Vitaliy Vorobyov, Aleksey Kovalev, Aleksandr Panov

DFormer: Rethinking RGBD Representation Learning for Semantic Segmentation Bowen Yin, Xuying Zhang, Zhong-Yu Li, Li Liu, Ming-Ming Cheng, Qibin Hou

Detecting Pretraining Data from Large Language Models Weijia Shi, Anirudh Ajith, Mengzhou Xia, Yangsibo Huang, Daogao Liu, Terra Blevins, Danqi Chen, Luke Zettlemoyer

Consistent4D: Consistent 360° Dynamic Object Generation from Monocular Video Yanqin Jiang, Li Zhang, Jin Gao, Weiming Hu, Yao Yao

DePT: Decomposed Prompt Tuning for Parameter-Efficient Fine-tuning Zhengxiang Shi, Aldo Lipani

Spoken Question Answering and Speech Continuation Using Spectrogram-Powered LLM Eliya Nachmani, Alon Levkovitch, Roy Hirsch, Julian Salazar, Chulayuth Asawaroengchai, Soroosh Mariooryad, Ehud Rivlin, RJ Skerry-Ryan, Michele Tadmor Ramanovich

Let Models Speak Ciphers: Multiagent Debate through Embeddings Chau Pham, Boyi Liu, Yingxiang Yang, Zhengyu Chen, Tianyi Liu, Jianbo Yuan, Bryan Plummer, Zhaoran Wang, Hongxia Yang

Analysis of Learning a Flow-based Generative Model from Limited Sample Complexity Hugo Cui, Florent Krzakala, Eric Vanden-Eijnden, Lenka Zdeborova

Learning Polynomial Problems with $SL(2, \mathbb{R})$-Equivariance Hannah Lawrence, Mitchell Harris

Node2ket: Efficient High-Dimensional Network Embedding in Quantum Hilbert Space Hao Xiong, Yehui Tang, Yunlin He, Wei Tan, Junchi Yan

Effective pruning of web-scale datasets based on complexity of concept clusters Amro Kamal, Evgenia Rusak, Kushal Tirumala, Wieland Brendel, Kamalika Chaudhuri, Ari Morcos

Teaching Language Models to Hallucinate Less with Synthetic Tasks Erik Jones, Hamid Palangi, Clarisse Ribeiro, Varun Chandrasekaran, Subhabrata Mukherjee, Arindam Mitra, Ahmed H Awadallah, Ece Kamar

Ghost on the Shell: An Expressive Representation of General 3D Shapes Zhen Liu, Yao Feng, Yuliang Xiu, Weiyang Liu, Liam Paull, Michael J Black, David Ha

FLATTEN: optical FLow-guided ATTENtion for consistent text-to-video editing Yuren Cong, Mengmeng Xu, Christian Simon, Shoufa Chen, Jiawei Ren, Yanping Xie, Juan-Manuel Perez-Rua, Bodo Rosenhahn, Tao Xiang, Sen He

Theoretical Analysis of Robust Overfitting for Wide DNNs: An NTK Approach Shaopeng Fu, Di Wang

Detecting Machine-Generated Texts by Multi-Population Aware Optimization for Maximum Mean Discrepancy Shuhai Zhang, Yiliao Song, Jiahao Yang, Yuanqing Li, Bo Han, Mingkui Tan

A Branching Decoder for Set Generation Zixian Huang, Gengyang Xiao, Yu Gu, Gong Cheng

SEINE: Short-to-Long Video Diffusion Model for Generative Transition and Prediction Xinyuan Chen, Yaohui Wang, Lingjun Zhang, Shaobin Zhuang, Xin Ma, Jiashuo Yu, Yali Wang, Dahua Lin, Yu Qiao, Ziwei Liu

Polynomial Width is Sufficient for Set Representation with High-dimensional Features Peihao Wang, Shenghao Yang, Shu Li, Zhangyang Wang, Pan Li

One Forward is Enough for Neural Network Training via Likelihood Ratio Method Jinyang Jiang, Zeliang Zhang, Chenliang Xu, Zhaofei Yu, Yijie Peng

VBH-GNN: Variational Bayesian Heterogeneous Graph Neural Networks for Cross-subject Emotion Recognition Chenyu Liu, XINLIANG ZHOU, Zhengri Zhu, Liming Zhai, Ziyu Jia, Yang Liu

Rethinking the symmetry-preserving circuits for constrained variational quantum algorithms Ge Yan, Hongxu Chen, Kaisen Pan, Junchi Yan

Shadow Cones: A Generalized Framework for Partial Order Embeddings Tao Yu, Toni Liu, Albert Tseng, Christopher De Sa

Magnitude Invariant Parametrizations Improve Hypernetwork Learning Jose Javier Gonzalez Ortiz, John Guttag, Adrian Dalca

EasyTPP: Towards Open Benchmarking Temporal Point Processes Siqiao Xue, Xiaoming Shi, Zhixuan Chu, Yan Wang, Hongyan Hao, Fan Zhou, caigao jiang, Chen Pan, James Zhang, Qingsong Wen, JUN ZHOU, Hongyuan Mei

A Restoration Network as an Implicit Prior Yuyang Hu, Mauricio Delbracio, Peyman Milanfar, Ulugbek Kamilov

QA-LoRA: Quantization-Aware Low-Rank Adaptation of Large Language Models Yuhui Xu, Lingxi Xie, Xiaotao Gu, Xin Chen, Heng Chang, Hengheng Zhang, Zhengsu Chen, XIAOPENG ZHANG, Qi Tian

SGD Finds then Tunes Features in Two-Layer Neural Networks with near-Optimal Sample Complexity: A Case Study in the XOR problem Margalit Glasgow

Respect the model: Fine-grained and Robust Explanation with Sharing Ratio Decomposition Sangyu Han, Yearim Kim, Nojun Kwak

Interpretable Meta-Learning of Physical Systems Matthieu Blanke, marc lelarge

CLIPSelf: Vision Transformer Distills Itself for Open-Vocabulary Dense Prediction Size Wu, Wenwei Zhang, Lumin Xu, Sheng Jin, Xiangtai Li, Wentao Liu, Chen Change Loy

Simplicial Representation Learning with Neural $k$-Forms Kelly Maggs, Celia Hacker, Bastian Rieck

Mayfly: a Neural Data Structure for Graph Stream Summarization yuan feng, Yukun Cao, Hairu Wang, Xike Xie, S Kevin Zhou

Aux-NAS: Exploiting Auxiliary Labels with Negligibly Extra Inference Cost Yuan Gao, WEIZHONG ZHANG, Wenhan Luo, Lin Ma, Jin-Gang Yu, Gui-Song Xia, Jiayi Ma

What does automatic differentiation compute for neural networks? Sejun Park, Sanghyuk Chun, Wonyeol Lee

Bayesian Neural Controlled Differential Equations for Treatment Effect Estimation Konstantin Hess, Valentyn Melnychuk, Dennis Frauen, Stefan Feuerriegel

Separate and Diffuse: Using a Pretrained Diffusion Model for Better Source Separation Shahar Lutati, Eliya Nachmani, Lior Wolf

The Hidden Language of Diffusion Models Hila Chefer, Oran Lang, Mor Geva, Volodymyr Polosukhin, Assaf Shocher, michal Irani, Inbar Mosseri, Lior Wolf

Trajeglish: Traffic Modeling as Next-Token Prediction Jonah Philion, Xue Bin Peng, Sanja Fidler

A Real-World WebAgent with Planning, Long Context Understanding, and Program Synthesis Izzeddin Gur, Hiroki Furuta, Austin Huang, Mustafa Safdari, Yutaka Matsuo, Douglas Eck, Aleksandra Faust

LoTa-Bench: Benchmarking Language-oriented Task Planners for Embodied Agents Jae-Woo Choi, Youngwoo Yoon, Hyobin Ong, Jaehong Kim, Minsu Jang

From Graphs to Hypergraphs: Hypergraph Projection and its Reconstruction Yanbang Wang, Jon Kleinberg

CLIP-MUSED: CLIP-Guided Multi-Subject Visual Neural Information Semantic Decoding Qiongyi Zhou, Changde Du, Shengpei Wang, Huiguang He

Asymptotically Free Sketched Ridge Ensembles: Risks, Cross-Validation, and Tuning Pratik Patil, Daniel LeJeune

Mixed-Type Tabular Data Synthesis with Score-based Diffusion in Latent Space Hengrui Zhang, Jiani Zhang, Zhengyuan Shen, Balasubramaniam Srinivasan, Xiao Qin, Christos Faloutsos, Huzefa Rangwala, George Karypis

Dual-Encoders for Extreme Multi-label Classification Nilesh Gupta, Fnu Devvrit, Ankit Singh Rawat, Srinadh Bhojanapalli, Prateek Jain, Inderjit Dhillon

Spike-driven Transformer V2: Meta Spiking Neural Network Architecture Inspiring the Design of Next-generation Neuromorphic Chips Man Yao, Jiakui Hu, Tianxiang Hu, Yifan Xu, Zhaokun Zhou, Yonghong Tian, Bo XU, Guoqi Li

TextField3D: Towards Enhancing Open-Vocabulary 3D Generation with Noisy Text Fields Tianyu Huang, Yihan Zeng, Bowen Dong, Hang Xu, Songcen Xu, Rynson W Lau, Wangmeng Zuo

GNNX-BENCH: Unravelling the Utility of Perturbation-based GNN Explainers through In-depth Benchmarking Mert Kosan, Samidha Verma, Burouj Armgaan, Khushbu Pahwa, Ambuj K Singh, Sourav Medya, Sayan Ranu

How to Fine-Tune Vision Models with SGD Ananya Kumar, Ruoqi Shen, Sebastien Bubeck, Suriya Gunasekar

AgentBench: Evaluating LLMs as Agents Xiao Liu, Hao Yu, Hanchen Zhang, Yifan Xu, Xuanyu Lei, Hanyu Lai, Yu Gu, Hangliang Ding, Kaiwen Men, Kejuan Yang, Shudan Zhang, Xiang Deng, Aohan Zeng, Zhengxiao Du, Chenhui Zhang, Sheng Shen, Tianjun Zhang, Yu Su, Huan Sun, Minlie Huang, Yuxiao Dong, Jie Tang

Consistency Models as a Rich and Efficient Policy Class for Reinforcement Learning Zihan Ding, Chi Jin

Progressive3D: Progressively Local Editing for Text-to-3D Content Creation with Complex Semantic Prompts Xinhua Cheng, Tianyu Yang, Jianan Wang, Yu Li, Lei Zhang, Jian Zhang, Yuan Li

Order-Preserving GFlowNets Yihang Chen, Lukas Mauch

Blending Imitation and Reinforcement Learning for Robust Policy Improvement Xuefeng Liu, Takuma Yoneda, Rick Stevens, Matthew Walter, Yuxin Chen

FLD: Fourier Latent Dynamics for Structured Motion Representation and Learning Chenhao Li, Elijah Stanger-Jones, Steve Heim, Sang bae Kim

Is attention required for ICL? Exploring the Relationship Between Model Architecture and In-Context Learning Ability Ivan Lee, Nan Jiang, Taylor Berg-Kirkpatrick

Reclaiming the Source of Programmatic Policies: Programmatic versus Latent Spaces Tales Carvalho, Kenneth Tjhia, Levi Lelis

FFB: A Fair Fairness Benchmark for In-Processing Group Fairness Methods Xiaotian Han, Jianfeng Chi, Yu Chen, Qifan Wang, Han Zhao, Na Zou, Xia Ben Hu

Beam Enumeration: Probabilistic Explainability For Sample Efficient Self-conditioned Molecular Design Jeff Guo, Philippe Schwaller

Zero and Few-shot Semantic Parsing with Ambiguous Inputs Elias Stengel-Eskin, Kyle Rawlins, Benjamin Van Durme

Continual Momentum Filtering on Parameter Space for Online Test-time Adaptation Jae-Hong Lee, Joon-Hyuk Chang

Noise-free Score Distillation Oren Katzir, Or Patashnik, Daniel Cohen-Or, Dani Lischinski

Adversarial Supervision Makes Layout-to-Image Diffusion Models Thrive Yumeng Li, Margret Keuper, Dan Zhang, Anna Khoreva

Online Stabilization of Spiking Neural Networks Yaoyu Zhu, Jianhao Ding, Tiejun Huang, Xiaodong Xie, Zhaofei Yu

MgNO: Efficient Parameterization of Linear Operators via Multigrid Juncai He, Xinliang Liu, Jinchao Xu

Locality Sensitive Sparse Encoding for Learning World Models Online Zichen Liu, Chao Du, Wee Sun Lee, Min Lin

Towards Principled Representation Learning from Videos for Reinforcement Learning Dipendra Kumar Misra, Akanksha Saran, Tengyang Xie, Alex Lamb, John Langford

Learning Adaptive Multiresolution Transforms via Meta-Framelet-based Graph Convolutional Network Tianze Luo, Zhanfeng Mo, Sinno Jialin Pan

Revisiting Data Augmentation in Deep Reinforcement Learning Jianshu Hu, Yunpeng Jiang, Paul Weng

The Hedgehog & the Porcupine: Expressive Linear Attentions with Softmax Mimicry Michael Zhang, Kush Bhatia, Hermann Kumbong, Christopher Re

Self-Consuming Generative Models Go MAD Sina Alemohammad, Josue Casco-Rodriguez, Lorenzo Luzi, Ahmed Imtiaz Humayun, Hossein Babaei, Daniel LeJeune, Ali Siahkoohi, Richard Baraniuk

On the Role of Discrete Tokenization in Visual Representation Learning Tianqi Du, Yifei Wang, Yisen Wang

Probabilistic Adaptation of Black-Box Text-to-Video Models Sherry Yang, Yilun Du, Bo Dai, Dale Schuurmans, Joshua B Tenenbaum, Pieter Abbeel

SalUn: Empowering Machine Unlearning via Gradient-based Weight Saliency in Both Image Classification and Generation Chongyu Fan, Jiancheng Liu, Yihua Zhang, Eric Wong, Dennis Wei, Sijia Liu

Beyond Weisfeiler-Lehman: A Quantitative Framework for GNN Expressiveness Bohang Zhang, Jingchu Gai, Yiheng Du, Qiwei Ye, Di He, Liwei Wang

FedDA: Faster Adaptive Gradient Methods for Federated Constrained Optimization Junyi Li, Feihu Huang, Heng Huang

A representation-learning game for classes of prediction tasks Neria Uzan, Nir Weinberger

SPTNet: An Efficient Alternative Framework for Generalized Category Discovery with Spatial Prompt Tuning Hongjun Wang, Sagar Vaze, Kai Han

SafeDreamer: Safe Reinforcement Learning with World Models Weidong Huang, Jiaming Ji, Chunhe Xia, Borong Zhang, Yaodong Yang

NfgTransformer: Equivariant Representation Learning for Normal-form Games Si-Qi Liu, Luke Marris, Georgios Piliouras, Ian Gemp, Nicolas Heess

Incentivized Truthful Communication for Federated Bandits Zhepei Wei, Chuanhao Li, Tianze Ren, Haifeng Xu, Hongning Wang

GPT-4 Is Too Smart To Be Safe: Stealthy Chat with LLMs via Cipher Youliang Yuan, Wenxiang Jiao, Wenxuan Wang, Jen-Tse Huang, Pinjia He, Shuming Shi, Zhaopeng Tu

Universal Backdoor Attacks Benjamin Schneider, Nils Lukas, Florian Kerschbaum

Rayleigh Quotient Graph Neural Networks for Graph-level Anomaly Detection Xiangyu Dong, Xingyi Zhang, Sibo WANG

Latent Representation and Simulation of Markov Processes via Time-Lagged Information Bottleneck Marco Federici, Patrick Forré, Ryota Tomioka, Bas Veeling

Domain-Agnostic Molecular Generation with Chemical Feedback Yin Fang, Ningyu Zhang, Zhuo Chen, Lingbing Guo, Xiaohui Fan, Huajun Chen

Understanding the Robustness of Randomized Feature Defense Against Query-Based Adversarial Attacks Hung Quang Nguyen, Yingjie Lao, Tung Pham, Kok-Seng Wong, Khoa Doan

SetCSE: Set Operations using Contrastive Learning of Sentence Embeddings Kang Liu

Large Language Models as Tool Makers Tianle Cai, Xuezhi Wang, Tengyu Ma, Xinyun Chen, Denny Zhou

InstructCV: Instruction-Tuned Text-to-Image Diffusion Models as Vision Generalists Yulu Gan, Sung Woo Park, Alexander Schubert, Anthony Philippakis, Ahmed Alaa

SWE-bench: Can Language Models Resolve Real-world Github Issues? Carlos E Jimenez, John Yang, Alexander Wettig, Shunyu Yao, Kexin Pei, Ofir Press, Karthik Narasimhan

DoLa: Decoding by Contrasting Layers Improves Factuality in Large Language Models Yung-Sung Chuang, Yujia Xie, Hongyin Luo, Yoon Kim, James R Glass, Pengcheng He

DeepSPF: Spherical SO(3)-Equivariant Patches for Scan-to-CAD Estimation Driton Salihu, Adam Misik, Yuankai Wu, Constantin Patsch, Fabian Seguel, Eckehard Steinbach

Horizon-Free Regret for Linear Markov Decision Processes Zihan Zhang, Jason Lee, Yuxin Chen, Simon Du

Label-Agnostic Forgetting: A Supervision-Free Unlearning in Deep Models Shaofei Shen, Chenhao Zhang, Yawen Zhao, Alina Bialkowski, Weitong Chen, Miao Xu

Neural Snowflakes: Universal Latent Graph Inference via Trainable Latent Geometries Haitz Sáez de Ocáriz Borde, Anastasis Kratsios

Variational Bayesian Last Layers James Harrison, John Willes, Jasper Snoek

True Knowledge Comes from Practice: Aligning Large Language Models with Embodied Environments via Reinforcement Learning Weihao Tan, Wentao Zhang, Shanqi Liu, Longtao Zheng, Xinrun Wang, Bo An

Learning invariant representations of time-homogeneous stochastic dynamical systems Vladimir Kostic, Pietro Novelli, Riccardo Grazzi, Karim Lounici, massimiliano pontil

Rethinking Label Poisoning for GNNs: Pitfalls and Attacks Vijay Chandra Lingam, Mohammad Sadegh Akhondzadeh, Aleksandar Bojchevski

Rephrase, Augment, Reason: Visual Grounding of Questions for Vision-Language Models Archiki Prasad, Elias Stengel-Eskin, Mohit Bansal

Learning Robust Generalizable Radiance Field with Visibility and Feature Augmented Point Representation Jiaxu Wang, Ziyi Zhang, Renjing Xu

Reinforcement Symbolic Regression Machine Yilong Xu, Yang Liu, Hao Sun

ControlVideo: Training-free Controllable Text-to-video Generation Yabo Zhang, Yuxiang Wei, Dongsheng jiang, XIAOPENG ZHANG, Wangmeng Zuo, Qi Tian

BRUSLEATTACK: A QUERY-EFFICIENT SCORE- BASED BLACK-BOX SPARSE ADVERSARIAL ATTACK Quoc Viet Vo, Ehsan Abbasnejad, Damith Ranasinghe

Pareto Deep Long-Tailed Recognition: A Conflict-Averse Solution Zhipeng Zhou, Liu Liu, Peilin Zhao, Wei Gong

DENEVIL: TOWARDS DECIPHERING AND NAVIGATING THE ETHICAL VALUES OF LARGE LANGUAGE MODELS VIA INSTRUCTION LEARNING Shitong Duan, Xiaoyuan Yi, Peng Zhang, Tun Lu, Xing Xie, Ning Gu

How to Catch an AI Liar: Lie Detection in Black-Box LLMs by Asking Unrelated Questions Lorenzo Pacchiardi, Alex Chan, Sören Mindermann, Ilan Moscovitz, Alexa Pan, Yarin Gal, Owain Evans, Jan Brauner

Statistical Rejection Sampling Improves Preference Optimization Tianqi Liu, Yao Zhao, Rishabh Joshi, Misha Khalman, Mohammad Saleh, Peter Liu, Jialu Liu

Test-Time Training on Nearest Neighbors for Large Language Models Moritz Hardt, Yu Sun

Adversarial Adaptive Sampling: Unify PINN and Optimal Transport for the Approximation of PDEs Kejun Tang, Jiayu Zhai, Xiaoliang Wan, Chao Yang

Towards LLM4QPE: Unsupervised Pretraining of Quantum Property Estimation and A Benchmark Yehui Tang, Hao Xiong, Nianzu Yang, Tailong Xiao, Junchi Yan

Massive Editing for Large Language Models via Meta Learning Chenmien Tan, Ge Zhang, Jie Fu

Efficient Dynamics Modeling in Interactive Environments with Koopman Theory Arnab Mondal, Siba Smarak Panigrahi, Sai Rajeswar, Kaleem Siddiqi, Siamak Ravanbakhsh

On Harmonizing Implicit Subpopulations Feng Hong, Jiangchao Yao, YUEMING LYU, Zhihan Zhou, Ivor Tsang, Ya Zhang, Yanfeng Wang

Domain-Inspired Sharpness-Aware Minimization Under Domain Shifts Ruipeng Zhang, Ziqing Fan, Jiangchao Yao, Ya Zhang, Yanfeng Wang

JointNet: Extending Text-to-Image Diffusion for Dense Distribution Modeling Jingyang Zhang, Shiwei Li, Yuanxun Lu, Tian Fang, David McKinnon, Yanghai Tsin, Long Quan, Yao Yao

MetaPhysiCa: Improving OOD Robustness in Physics-informed Machine Learning S Chandra Mouli, Muhammad Alam, Bruno Ribeiro

Guiding Instruction-based Image Editing via Multimodal Large Language Models Tsu-Jui Fu, Wenze Hu, Xianzhi Du, William Wang, Yinfei Yang, Zhe Gan

A differentiable brain simulator bridging brain simulation and brain-inspired computing Chaoming Wang, Tianqiu Zhang, Sichao He, Hongyaoxing Gu, Shangyang Li, Si Wu

Understanding Addition in Transformers Philip Quirke, Fazl Barez

An operator preconditioning perspective on training in physics-informed machine learning Tim De Ryck, Florent Bonnet, Siddhartha Mishra, Emmanuel de Bézenac

Composed Image Retrieval with Text Feedback via Multi-grained Uncertainty Regularization Yiyang Chen, Zhedong Zheng, Wei Ji, Leigang Qu, Tat-Seng Chua

DSPy: Compiling Declarative Language Model Calls into State-of-the-Art Pipelines Omar Khattab, Arnav Singhvi, Paridhi Maheshwari, Zhiyuan Zhang, Keshav Santhanam, Sri Vardhamanan A, Saiful Haq, Ashutosh Sharma, Thomas Joshi, Hanna Moazam, Heather Miller, Matei Zaharia, Christopher Potts

Dynamics-Informed Protein Design with Structure Conditioning Urszula Julia Komorowska, Simon Mathis, Kieran Didi, Francisco Vargas, Pietro Lio, Mateja Jamnik

Teach LLMs to Phish: Stealing Private Information from Language Models Ashwinee Panda, Christopher Choquette-Choo, Zhengming Zhang, Yaoqing Yang, Prateek Mittal

Improving Convergence and Generalization Using Parameter Symmetries Bo Zhao, Robert M. Gower, Robin Walters, Rose Yu

Test-time Adaptation against Multi-modal Reliability Bias Mouxing Yang, Yunfan Li, Changqing Zhang, Peng Hu, Xi Peng

Symmetric Mean-field Langevin Dynamics for Distributional Minimax Problems Juno Kim, Kakei Yamamoto, Kazusato Oko, Zhuoran Yang, Taiji Suzuki

Tensor Programs VI: Feature Learning in Infinite Depth Neural Networks Greg Yang, Dingli Yu, Chen Zhu, Soufiane Hayou

A Simple Interpretable Transformer for Fine-Grained Image Classification and Analysis DIPANJYOTI PAUL, Arpita Chowdhury, Xinqi Xiong, Feng-Ju Chang, David Carlyn, Samuel Stevens, Kaiya Provost, Anuj Karpatne, Bryan Carstens, Daniel Rubenstein, Charles Stewart, Tanya Berger-Wolf, Yu Su, Wei-Lun Chao

Conformal Inductive Graph Neural Networks Soroush H. Zargarbashi, Aleksandar Bojchevski

Conformal Risk Control Anastasios Angelopoulos, Stephen Bates, Adam Fisch, Lihua Lei, Tal Schuster

Critical Learning Periods Emerge Even in Deep Linear Networks Michael Kleinman, Alessandro Achille, Stefano Soatto

Transport meets Variational Inference: Controlled Monte Carlo Diffusions Francisco Vargas, Shreyas Padhy, Denis Blessing, Nikolas Nüsken

Interpretable Diffusion via Information Decomposition Xianghao Kong, Ollie Liu, Han Li, Dani Yogatama, Greg Ver Steeg

CrossQ: Batch Normalization in Deep Reinforcement Learning for Greater Sample Efficiency and Simplicity Aditya Bhatt, Daniel Palenicek, Boris Belousov, Max Argus, Artemij Amiranashvili, Thomas Brox, Jan Peters

TOSS: High-quality Text-guided Novel View Synthesis from a Single Image Yukai Shi, Jianan Wang, He CAO, Boshi Tang, Xianbiao Qi, Tianyu Yang, Yukun Huang, Shilong Liu, Lei Zhang, Heung-Yeung Shum

Parallelizing non-linear sequential models over the sequence length Yi Heng Lim, Qi Zhu, Joshua Selfridge, Muhammad Firmansyah

FLASK: Fine-grained Language Model Evaluation based on Alignment Skill Sets Seonghyeon Ye, Doyoung Kim, Sungdong Kim, Hyeonbin Hwang, Seungone Kim, Yongrae Jo, James Thorne, Juho Kim, Minjoon Seo

Understanding Transferable Representation Learning and Zero-shot Transfer in CLIP Zixiang Chen, Yihe Deng, Yuanzhi Li, Quanquan Gu

What's in a Prior? Learned Proximal Networks for Inverse Problems Zhenghan Fang, Sam Buchanan, Jeremias Sulam

Towards Generative Abstract Reasoning: Completing Raven’s Progressive Matrix via Rule Abstraction and Selection Fan Shi, Bin Li, Xiangyang Xue

Beyond Worst-case Attacks: Robust RL with Adaptive Defense via Non-dominated Policies Xiangyu Liu, Chenghao Deng, Yanchao Sun, Yongyuan Liang, Furong Huang

Multimodal Patient Representation Learning with Missing Modalities and Labels Zhenbang Wu, Anant Dadu, Nicholas Tustison, Brian Avants, Michael Nalls, Jimeng Sun, Faraz Faghri

Maximum Likelihood Estimation is All You Need for Well-Specified Covariate Shift Jiawei Ge, Shange Tang, Jianqing Fan, Cong Ma, Chi Jin

An Analytical Solution to Gauss-Newton Loss for Direct Image Alignment Sergei Solonets, Daniil Sinitsyn, Lukas Von Stumberg, Nikita Araslanov, Daniel Cremers

Chain-of-Table: Evolving Tables in the Reasoning Chain for Table Understanding Zilong (Ryan) Wang, Hao Zhang, Chun-Liang Li, Julian M Eisenschlos, Vincent Perot, Zifeng Wang, Lesly Miculicich, Yasuhisa Fujii, Jingbo Shang, Chen-Yu Lee, Tomas Pfister

Spatio-Temporal Few-Shot Learning via Diffusive Neural Network Generation Yuan Yuan, Chenyang Shao, Jingtao Ding, Depeng Jin, Yong Li

SparseFormer: Sparse Visual Recognition via Limited Latent Tokens Ziteng Gao, Zhan Tong, Limin Wang, Mike Zheng Shou

Threaten Spiking Neural Networks through Combining Rate and Temporal Information Zecheng Hao, Tong Bu, Xinyu Shi, Zihan Huang, Zhaofei Yu, Tiejun Huang

PRES: Toward Scalable Memory-Based Dynamic Graph Neural Networks Junwei Su, Difan Zou, Chuan Wu

Multi-View Representation is What You Need for Point-Cloud Pre-Training Siming Yan, Chen Song, Youkang Kong, Qixing Huang

USB-NeRF: Unrolling Shutter Bundle Adjusted Neural Radiance Fields Moyang Li, Peng Wang, Lingzhe Zhao, Bangyan Liao, Peidong Liu

$\mathbb{D}^2$ Pruning: Message Passing for Balancing Diversity & Difficulty in Data Pruning Adyasha Maharana, Prateek Yadav, Mohit Bansal

Topic Modeling as Multi-Objective Contrastive Optimization Thong Thanh Nguyen, Xiaobao Wu, Xinshuai Dong, Cong-Duy Nguyen, See-Kiong Ng, Anh Tuan Luu

SPDER: Semiperiodic Damping-Enabled Object Representation Kathan Shah, Chawin Sitawarin

UNR-Explainer: Counterfactual Explanations for Unsupervised Node Representation Learning Models Hyunju Kang, Geonhee Han, Hogun Park

Symmetric Neural-Collapse Representations with Supervised Contrastive Loss: The Impact of ReLU and Batching Ganesh Ramachandra Kini, Vala Vakilian, Tina Behnia, Jaidev Gill, Christos Thrampoulidis

Human Feedback is not Gold Standard Tom Hosking, Phil Blunsom, Max Bartolo

Multimarginal Generative Modeling with Stochastic Interpolants Michael Albergo, Nicholas Boffi, Michael Lindsey, Eric Vanden-Eijnden

GNNBoundary: Towards Explaining Graph Neural Networks through the Lens of Decision Boundaries Xiaoqi Wang, Han Wei Shen

AutomaTikZ: Text-Guided Synthesis of Scientific Vector Graphics with TikZ Jonas Belouadi, Anne Lauscher, Steffen Eger

InstructPix2NeRF: Instructed 3D Portrait Editing from a Single Image Jianhui Li, Shilong Liu, Zidong Liu, Yikai Wang, Kaiwen Zheng, Jinghui Xu, Jianmin Li, Jun Zhu

Towards Cheaper Inference in Deep Networks with Lower Bit-Width Accumulators Yaniv Blumenfeld, Itay Hubara, Daniel Soudry

Accelerated Convergence of Stochastic Heavy Ball Method under Anisotropic Gradient Noise Rui Pan, Yuxing Liu, Xiaoyu Wang, Tong Zhang

Procedural Fairness Through Decoupling Objectionable Data Generating Components Zeyu Tang, Jialu Wang, Yang Liu, Peter Spirtes, Kun Zhang

BooookScore: A systematic exploration of book-length summarization in the era of LLMs Yapei Chang, Kyle Lo, Tanya Goyal, Mohit Iyyer

Understanding In-Context Learning in Transformers and LLMs by Learning to Learn Discrete Functions Satwik Bhattamishra, Arkil Patel, Phil Blunsom, Varun Kanade

OPTIMAL ROBUST MEMORIZATION WITH RELU NEURAL NETWORKS Lijia Yu, XIAOSHAN GAO, Lijun Zhang

AutoDAN: Generating Stealthy Jailbreak Prompts on Aligned Large Language Models Xiaogeng Liu, Nan Xu, Muhao Chen, Chaowei Xiao

Robust Model-Based Optimization for Challenging Fitness Landscapes Saba Ghaffari, Ehsan Saleh, Alex Schwing, Yu-Xiong Wang, Martin Burke, Saurabh Sinha

DrM: Mastering Visual Reinforcement Learning through Dormant Ratio Minimization Guowei Xu, Ruijie Zheng, Yongyuan Liang, Xiyao Wang, Zhecheng Yuan, Tianying Ji, Yu Luo, Xiaoyu Liu, Jiaxin Yuan, Pu Hua, Shuzhen Li, Yanjie Ze, Hal Daumé III, Furong Huang, Huazhe Xu

Butterfly Effects of SGD Noise: Error Amplification in Behavior Cloning and Autoregression Adam Block, Dylan Foster, Akshay Krishnamurthy, Max Simchowitz, Cyril Zhang

Efficient Subgraph GNNs by Learning Effective Selection Policies Beatrice Bevilacqua, Moshe Eliasof, Eli Meirom, Bruno Ribeiro, Haggai Maron

In-Context Learning Dynamics with Random Binary Sequences Eric Bigelow, Ekdeep Singh Lubana, Robert Dick, Hidenori Tanaka, Tomer Ullman

Generative Learning for Financial Time Series with Irregular and Scale-Invariant Patterns Hongbin Huang, Minghua Chen, Xiao Qiao

Meta-Learning Priors Using Unrolled Proximal Networks Yilang Zhang, Georgios B Giannakis

Geometrically Aligned Transfer Encoder for Inductive Transfer in Regression Tasks Sung Moon Ko, Sumin Lee, Dae-Woong Jeong, Woohyung Lim, Sehui Han

Energy-conserving equivariant GNN for elasticity of lattice architected metamaterials Ivan Grega, Ilyes Batatia, Gábor Csányi, Sri Karlapati, Vikram Deshpande

Decoupling regularization from the action space Sobhan Mohammadpour, Emma Frejinger, Pierre-Luc Bacon

Theoretical Understanding of Learning from Adversarial Perturbations Soichiro Kumano, Hiroshi Kera, Toshihiko Yamasaki

Learning in reverse causal strategic environments with ramifications on two sided markets Seamus Somerstep, Yuekai Sun, Yaacov Ritov

SelfCheck: Using LLMs to Zero-Shot Check Their Own Step-by-Step Reasoning Ning Miao, Yee Whye Teh, Tom Rainforth

Learning From Simplicial Data Based on Random Walks and 1D Convolutions Florian Frantzen, Michael Schaub

How Many Pretraining Tasks Are Needed for In-Context Learning of Linear Regression? Jingfeng Wu, Difan Zou, Zixiang Chen, Vladimir Braverman, Quanquan Gu, Peter Bartlett

Consciousness-Inspired Spatio-Temporal Abstractions for Better Generalization in Reinforcement Learning Mingde Zhao, Safa Alver, Harm Seijen, Romain Laroche, Doina Precup, Yoshua Bengio

AntGPT: Can Large Language Models Help Long-term Action Anticipation from Videos? Qi Zhao, Shijie Wang, Ce Zhang, Changcheng Fu, Minh Quan Do, Nakul Agarwal, Kwonjoon Lee, Chen Sun

Multilinear Operator Networks Yixin Cheng, Grigorios Chrysos, Markos Georgopoulos, Volkan Cevher

LiDAR: Sensing Linear Probing Performance in Joint Embedding SSL Architectures Vimal Thilak, Chen Huang, Omid Saremi, Laurent Dinh, Hanlin Goh, Preetum Nakkiran, Joshua Susskind, Etai Littwin

Universal Humanoid Motion Representations for Physics-Based Control Zhengyi Luo, Jinkun Cao, Josh Merel, Alexander Winkler, Jing Huang, Kris Kitani, Weipeng Xu

AnyText: Multilingual Visual Text Generation and Editing Yuxiang Tuo, Wangmeng Xiang, Jun-Yan He, Yifeng Geng, Xuansong Xie

Inherently Interpretable Time Series Classification via Multiple Instance Learning Joseph Early, Gavin Cheung, Kurt Cutajar, Hanting Xie, Jas Kandola, Niall Twomey

Sample-Efficient Quality-Diversity by Cooperative Coevolution Ke Xue, Ren-Jian Wang, Pengyi Li, Dong Li, Jianye HAO, Chao Qian

A Sublinear Adversarial Training Algorithm Yeqi Gao, Lianke Qin, Zhao Song, Yitan Wang

Diagnosing Transformers: Illuminating Feature Spaces for Clinical Decision-Making Aliyah Hsu, Yeshwanth Cherapanamjeri, Briton Park, Tristan Naumann, Anobel Odisho, Bin Yu

Understanding Expressivity of GNN in Rule Learning Haiquan Qiu, Yongqi Zhang, Yong Li, Quanming Yao

Scalable Neural Network Kernels Arijit Sehanobish, Krzysztof Choromanski, YUNFAN ZHAO, Kumar Dubey, Valerii Likhosherstov

Analyzing and Mitigating Object Hallucination in Large Vision-Language Models Yiyang Zhou, Chenhang Cui, Jaehong Yoon, Linjun Zhang, Zhun Deng, Chelsea Finn, Mohit Bansal, Huaxiu Yao

Towards Lossless Dataset Distillation via Difficulty-Aligned Trajectory Matching Ziyao Guo, Kai Wang, George Cazenavette, HUI LI, Kaipeng Zhang, Yang You

OpenChat: Advancing Open-source Language Models with Mixed-Quality Data Guan Wang, Sijie Cheng, Xianyuan Zhan, Xiangang Li, Sen Song, Yang Liu

Extending Power of Nature from Binary to Real-Valued Graph Learning in Real World Chunshu Wu, Ruibing Song, Chuan Liu, Yunan Yang, Ang Li, Michael Huang, Tong Geng

Heterogeneous Personalized Federated Learning by Local-Global Updates Mixing via Convergence Rate Meirui Jiang, Anjie Le, Xiaoxiao Li, Qi Dou

Dynamic Layer Tying for Parameter-Efficient Transformers Tamir David-Hay, Lior Wolf

Dynamic Neighborhood Construction for Structured Large Discrete Action Spaces Fabian Akkerman, Julius Luy, Wouter van Heeswijk, Maximilian Schiffer

Prioritized Soft Q-Decomposition for Lexicographic Reinforcement Learning Finn Rietz, Erik Schaffernicht, Stefan Heinrich, Johannes A. Stork

Ferret: Refer and Ground Anything Anywhere at Any Granularity Haoxuan You, Haotian Zhang, Zhe Gan, Xianzhi Du, Bowen Zhang, Zirui Wang, Liangliang Cao, Shih-Fu Chang, Yinfei Yang

Making RL with Preference-based Feedback Efficient via Randomization Runzhe Wu, Wen Sun

Novel Quadratic Constraints for Extending LipSDP beyond Slope-Restricted Activations Patricia Pauli, Aaron Havens, Alexandre Araujo, Siddharth Garg, Farshad Khorrami, Frank Allgöwer, Bin Hu

Waxing-and-Waning: a Generic Similarity-based Framework for Efficient Self-Supervised Learning Sheng Li, Chao Wu, Ao Li, Yanzhi Wang, Xulong Tang, Geng Yuan

Pooling Image Datasets with Multiple Covariate Shift and Imbalance Sotirios Panagiotis Chytas, Vishnu Lokhande, Vikas Singh

Adaptive Retrieval and Scalable Indexing for k-NN Search with Cross-Encoders Nishant Yadav, Nicholas Monath, Manzil Zaheer, Rob Fergus, Andrew McCallum

Maximum Entropy Heterogeneous-Agent Reinforcement Learning Jiarong Liu, Yifan Zhong, Siyi Hu, Haobo Fu, QIANG FU, Xiaojun Chang, Yaodong Yang

Gaining Wisdom from Setbacks: Aligning Large Language Models via Mistake Analysis Kai Chen, Chunwei Wang, Kuo Yang, Jianhua Han, Lanqing HONG, Fei Mi, Hang Xu, Zhengying Liu, Wenyong Huang, Zhenguo Li, Dit-Yan Yeung, Lifeng Shang

Federated Q-Learning: Linear Regret Speedup with Low Communication Cost Zhong Zheng, Fengyu Gao, Lingzhou Xue, Jing Yang

Self-Supervised Dataset Distillation for Transfer Learning Dong Bok Lee, Seanie Lee, Joonho Ko, Kenji Kawaguchi, Juho Lee, Sung Ju Hwang

Hindsight PRIORs for Reward Learning from Human Preferences Mudit Verma, Katherine Metcalf

Efficient Modulation for Vision Networks Xu Ma, Xiyang Dai, Jianwei Yang, Bin Xiao, Yinpeng Chen, Yun Fu, Lu Yuan

PAC-FNO: Parallel-Structured All-Component Fourier Neural Operators for Recognizing Low-Quality Images Jinsung Jeon, Hyundong Jin, Jonghyun Choi, Sanghyun Hong, Dongeun Lee, Kookjin Lee, Noseong Park

Neural Active Learning Beyond Bandits Yikun Ban, Ishika Agarwal, Ziwei Wu, Yada Zhu, Kommy Weldemariam, Hanghang Tong, Jingrui He

Causal Modelling Agents: Causal Graph Discovery through Synergising Metadata- and Data-driven Reasoning Ahmed Abdulaal, Adamos Hadjivasiliou, Nina Montaña-Brown, Tiantian He, Ayodeji Ijishakin, Ivana Drobnjak, Daniel Castro, Daniel Alexander

PixArt-$\alpha$: Fast Training of Diffusion Transformer for Photorealistic Text-to-Image Synthesis Junsong Chen, Jincheng YU, Chongjian GE, Lewei Yao, Enze Xie, Zhongdao Wang, James Kwok, Ping Luo, Huchuan Lu, Zhenguo Li

Sparse Model Soups: A Recipe for Improved Pruning via Model Averaging Max Zimmer, Christoph Spiegel, Sebastian Pokutta

PromptTTS 2: Describing and Generating Voices with Text Prompt Yichong Leng, ZHifang Guo, Kai Shen, Zeqian Ju, Xu Tan, Eric Liu, Yufei Liu, Dongchao Yang, leying zhang, Kaitao Song, Lei He, Xiangyang Li, sheng zhao, Tao Qin, Jiang Bian

Mitigating Hallucination in Large Multi-Modal Models via Robust Instruction Tuning Fuxiao Liu, Kevin Lin, Linjie Li, Jianfeng Wang, Yaser Yacoob, Lijuan Wang

CRITIC: Large Language Models Can Self-Correct with Tool-Interactive Critiquing Zhibin Gou, Zhihong Shao, Yeyun Gong, yelong shen, Yujiu Yang, Nan Duan, Weizhu Chen

Counterfactual Density Estimation using Kernel Stein Discrepancies Diego Martinez-Taboada, Edward Kennedy

Adversarial Training Should Be Cast as a Non-Zero-Sum Game Alex Robey, Fabian Latorre, George Pappas, Hamed Hassani, Volkan Cevher

Can we get the best of both Binary Neural Networks and Spiking Neural Networks for Efficient Computer Vision? Gourav Datta, Zeyu Liu, Peter Beerel

An Efficient Membership Inference Attack for the Diffusion Model by Proximal Initialization Fei Kong, Jinhao Duan, ruipeng ma, Heng Tao Shen, Xiaoshuang Shi, Xiaofeng Zhu, Kaidi Xu

Like Oil and Water: Group Robustness Methods and Poisoning Defenses May Be at Odds Michael-Andrei Panaitescu-Liess, Yigitcan Kaya, Sicheng Zhu, Furong Huang, Tudor Dumitras

Mega-TTS 2: Boosting Prompting Mechanisms for Zero-Shot Speech Synthesis Ziyue Jiang, Jinglin Liu, Yi Ren, Jinzheng He, Zhenhui Ye, Shengpeng Ji, Qian Yang, Chen Zhang, Pengfei Wei, Chunfeng Wang, Xiang Yin, Zejun MA, Zhou Zhao

FedWon: Triumphing Multi-domain Federated Learning Without Normalization Weiming Zhuang, Lingjuan Lyu

Group Preference Optimization: Few-Shot Alignment of Large Language Models Siyan Zhao, John Dang, Aditya Grover

ReSimAD: Zero-Shot 3D Domain Transfer for Autonomous Driving with Source Reconstruction and Target Simulation Bo Zhang, Xinyu Cai, Jiakang Yuan, Donglin Yang, Jianfei Guo, Xiangchao Yan, Renqiu Xia, Botian Shi, Min Dou, Tao Chen, Si Liu, Junchi Yan, Yu Qiao

DP-OPT: Make Large Language Model Your Privacy-Preserving Prompt Engineer Junyuan Hong, Jiachen (Tianhao) Wang, Chenhui Zhang, Zhangheng LI, Bo Li, Zhangyang Wang

International Conference on Representation Learning 2024 (ICLR 2024)

Name Change Policy