@misc{BEIR2021,
      title={BEIR: A Heterogenous Benchmark for Zero-shot Evaluation of Information Retrieval Models}, 
      author={Nandan Thakur and Nils Reimers and Andreas Rücklé and Abhishek Srivastava and Iryna Gurevych},
      year={2021},
      eprint={2104.08663},
      archivePrefix={arXiv},
      primaryClass={cs.IR},
      url={https://arxiv.org/abs/2104.08663}, 
}

@article{Sebastiani2002TextCat,
  author  = {Fabrizio Sebastiani},
  title   = {Machine Learning in Automated Text Categorization},
  journal = {ACM Computing Surveys},
  volume  = {34},
  number  = {1},
  pages   = {1--47},
  year    = {2002}
}

@article{Kowsari2019Survey,
  author  = {Kamran Kowsari and Kiana Jafari Meimandi and Mojtaba Heidarysafa and
             Sanjana Mendu and Laura~E. Barnes and Donald~E. Brown},
  title   = {Text Classification Algorithms: A Survey},
  journal = {Information},
  volume  = {10},
  number  = {4},
  pages   = {150},
  year    = {2019},
  doi     = {10.3390/info10040150}
}

@techreport{Settles2012ActiveLearning,
  author      = {Burr Settles},
  title       = {Active Learning Literature Survey},
  institution = {University of Wisconsin--Madison},
  number      = {1648},
  year        = {2012},
  url         = {https://burrsettles.com/pub/settles.activelearning.pdf}
}

@inproceedings{Yin2019ZSC,
  author    = {Wenpeng Yin and Jamaal Hay and Dan Roth},
  title     = {Benchmarking Zero-shot Text Classification: Datasets, Evaluation and Entailment Approach},
  booktitle = {Proc.\ EMNLP--IJCNLP},
  pages     = {3914--3923},
  year      = {2019}
}

@article{Brown2020GPT3,
  author  = {Tom~B. Brown and Benjamin Mann and Nick Ryder and Melanie Subbiah and
             Jared Kaplan and \emph{et al.}},
  title   = {Language Models are Few-Shot Learners},
  journal = {arXiv preprint arXiv:2005.14165},
  year    = {2020}
}

@inproceedings{Reimers2019SBERT,
  author    = {Nils Reimers and Iryna Gurevych},
  title     = {Sentence-{BERT}: Sentence Embeddings using Siamese {BERT}-Networks},
  booktitle = {Proc.\ EMNLP},
  year      = {2019}
}

@inproceedings{Gao2021SimCSE,
  author    = {Tianyu Gao and Xingcheng Yao and Danqi Chen},
  title     = {SimCSE: Simple Contrastive Learning of Sentence Embeddings},
  booktitle = {Proc.\ EMNLP},
  pages     = {6894--6910},
  year      = {2021}
}

@inproceedings{Bowman2015SNLI,
  author    = {Samuel~R. Bowman and Gabor Angeli and Christopher Potts and
               Christopher~D. Manning},
  title     = {A Large Annotated Corpus for Learning Natural Language Inference},
  booktitle = {Proc.\ EMNLP},
  pages     = {632--642},
  year      = {2015}
}

@inproceedings{Williams2018MNLI,
  author    = {Adina Williams and Nikita Nangia and Samuel Bowman},
  title     = {A Broad-Coverage Challenge Corpus for Sentence Understanding through Inference},
  booktitle = {Proc.\ NAACL-HLT},
  pages     = {1112--1122},
  year      = {2018}
}

@inproceedings{Muennighoff2023MTEB,
  author    = {Niklas Muennighoff and Nouamane Tazi and Loic Magne and Nils Reimers},
  title     = {{MTEB}: Massive Text Embedding Benchmark},
  booktitle = {Proc.\ EACL},
  pages     = {2014--2037},
  year      = {2023}
}

@article{Nogueira2020MonoT5,
  author  = {Rodrigo Nogueira and Zhiying Jiang and Jimmy Lin},
  title   = {Document Ranking with a Pretrained Sequence-to-Sequence Model},
  journal = {arXiv preprint arXiv:2003.06713},
  year    = {2020}
}

@article{Ni2021SentenceT5,
  author  = {Jianmo Ni and Gustavo Hern{\'a}ndez {\'A}brego and Noah Constant and
             Ji Ma and Keith~B. Hall and Daniel Cer and Yinfei Yang},
  title   = {Sentence-{T5}: Scalable Sentence Encoders from Pre-trained Text-to-Text Models},
  journal = {arXiv preprint arXiv:2108.08877},
  year    = {2021}
}

@article{Wang2024E5,
  author  = {Liang Wang and Nan Yang and Xiaolong Huang and Linjun Yang and
             Rangan Majumder and Furu Wei},
  title   = {Multilingual {E5} Text Embeddings: A Technical Report},
  journal = {arXiv preprint arXiv:2402.05672},
  year    = {2024}
}

@inproceedings{Chalkidis2020LMTC,
  author    = {Ilias Chalkidis and Manos Fergadiotis and Sotiris Kotitsas and
               Prodromos Malakasiotis and Nikolaos Aletras and Ion Androutsopoulos},
  title     = {An Empirical Study on Large-Scale Multi-Label Text Classification Including Few and Zero-Shot Labels},
  booktitle = {Proceedings of EMNLP},
  year      = {2020}
}

@inproceedings{Gretz2023TTC,
  author    = {Shai Gretz and Alon Halfon and Ilya Shnayderman and Orith Toledo-Ronen and Artem Spector and Lena Dankin and Yannis Katsis and Ofir Arviv and Yoav Katz and Noam Slonim and Liat Ein-Dor},
  title     = {Zero-shot Topical Text Classification with LLMs -- an Experimental Study},
  booktitle = {Findings of EMNLP},
  pages     = {9647--9676},
  year      = {2023}
}

@inproceedings{Lepagnol2024SmallLM,
  author    = {Pierre Lepagnol and Thomas Gerald and Sahar Ghannay and Christophe Servan and Sophie Rosset},
  title     = {Small Language Models are Good Too: An Empirical Study of Zero-Shot Classification},
  booktitle = {Proceedings of LREC–COLING},
  year      = {2024}
}

@article{Li2023GTE,
  author  = {Zehan Li and Xin Zhang and Yanzhao Zhang and Dingkun Long and Pengjun Xie and Meishan Zhang},
  title   = {Towards General Text Embeddings with Multi-stage Contrastive Learning},
  journal = {arXiv preprint arXiv:2308.03281},
  year    = {2023}
}

@article{Chen2024BGE,
  author  = {Jianlv Chen and Shitao Xiao and Peitian Zhang and Kun Luo and Defu Lian and Zheng Liu},
  title   = {BGE M3-Embedding: Multi-Lingual, Multi-Functionality, Multi-Granularity Text Embeddings Through Self-Knowledge Distillation},
  journal = {arXiv preprint arXiv:2402.03216},
  year    = {2024}
}

@article{Zhang2025Qwen3Embedding,
  author  = {Yanzhao Zhang and Mingxin Li and Dingkun Long and Xin Zhang and Huan Lin and others},
  title   = {Qwen3 Embedding: Advancing Text Embedding and Reranking Through Foundation Models},
  journal = {arXiv preprint arXiv:2506.05176},
  year    = {2025}
}

@article{Enevoldsen2025MMTEB,
  author  = {Kenneth Enevoldsen and Isaac Chung and Imene Kerboua and Márton Kardos and Ashwin Mathur and others},
  title   = {MMTEB: Massive Multilingual Text Embedding Benchmark},
  journal = {arXiv preprint arXiv:2502.13595},
  year    = {2025}
}

@article{Chung2025MaintainMTEB,
  author  = {Isaac Chung and Imene Kerboua and Marton Kardos and Roman Solomatin and Kenneth Enevoldsen},
  title   = {Maintaining MTEB: Towards Long Term Usability and Reproducibility of Embedding Benchmarks},
  journal = {arXiv preprint arXiv:2506.21182},
  year    = {2025}
}

@inproceedings{Mikolov2013Word2Vec,
  author    = {Tomas Mikolov and Kai Chen and Greg Corrado and Jeffrey Dean},
  title     = {Efficient Estimation of Word Representations in Vector Space},
  booktitle = {ICLR Workshop},
  year      = {2013}
}

@inproceedings{Conneau2017InferSent,
  author    = {Alexis Conneau and Douwe Kiela and Holger Schwenk and Loïc Barrault and Antoine Bordes},
  title     = {Supervised Learning of Universal Sentence Representations from Natural Language Inference Data},
  booktitle = {Proceedings of EMNLP},
  year      = {2017}
}

@inproceedings{Cer2018USE,
  author    = {Daniel Cer and Yinfei Yang and Sheng-yi Kong and Nan Hua and Nicole Limtiaco and others},
  title     = {Universal Sentence Encoder},
  booktitle = {Proceedings of EMNLP},
  year      = {2018}
}

@inproceedings{Devlin2019BERT,
  author    = {Jacob Devlin and Ming-Wei Chang and Kenton Lee and Kristina Toutanova},
  title     = {BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding},
  booktitle = {Proceedings of NAACL-HLT},
  year      = {2019}
}

@inproceedings{Karpukhin2020DPR,
  author    = {Vladimir Karpukhin and Barlas Oğuz and Sewon Min and Patrick Lewis and Ledell Wu and Sergey Edunov and Danqi Chen and Wen-tau Yih},
  title     = {Dense Passage Retrieval for Open-Domain Question Answering},
  booktitle = {Proceedings of EMNLP},
  year      = {2020}
}

@inproceedings{Khattab2020ColBERT,
  author    = {Omar Khattab and Matei Zaharia},
  title     = {ColBERT: Efficient and Effective Passage Search via Contextualized Late Interaction over BERT},
  booktitle = {Proceedings of SIGIR},
  year      = {2020}
}

@inproceedings{Lewis2020BART,
  author    = {Mike Lewis and Yinhan Liu and Naman Goyal and Marjan Ghazvininejad and Abdelrahman Mohamed and Omer Levy and Ves Stoyanov and Luke Zettlemoyer},
  title     = {BART: Denoising Sequence-to-Sequence Pre-training for Natural Language Generation, Translation, and Comprehension},
  booktitle = {Proceedings of ACL},
  year      = {2020}
}

@inproceedings{Radford2021CLIP,
  title     = {Learning Transferable Visual Models From Natural Language Supervision},
  author    = {Alec Radford and Jong Wook Kim and Chris Hallacy and Aditya Ramesh and Gabriel Goh and Sandhini Agarwal and Girish Sastry and Amanda Askell and Pamela Mishkin and Jack Clark and Gretchen Krueger and Ilya Sutskever},
  booktitle = {Proceedings of the 38th International Conference on Machine Learning (ICML)},
  year      = {2021},
  month     = {July},
  publisher = {PMLR},
}

@inproceedings{He2023DeBERTaV3,
  author    = {Pengcheng He and Jianfeng Gao and Weizhu Chen},
  title     = {{DeBERTaV3}: Improving {DeBERTa} using {ELECTRA}-Style Pre-Training with Gradient-Disentangled Embedding Sharing},
  booktitle = {Proc.\ International Conference on Learning Representations (ICLR)},
  year      = {2023},
  url       = {https://openreview.net/forum?id=sE7-XhLxHA},
  note      = {arXiv:2111.09543}
}

@inproceedings{HF2020Transformers,
  title       = {Transformers: State-of-the-Art Natural Language Processing},
  author      = {Thomas Wolf and Lysandre Debut and Victor Sanh and Julien Chaumond and
                 Cl{\'e}ment Delangue and Anthony Moi and Pierric Cistac and Tim Rault and
                 R{\'e}mi Louf and Morgan Funtowicz and Joe Davison and Sam Shleifer and
                 Patrick von Platen and Clara Ma and Yacine Jernite and Julien Plu and
                 Canwen Xu and Teven Le Scao and Sylvain Gugger and Mariama Drame and
                 Quentin Lhoest and Alexander M. Rush},
  booktitle   = {Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing: System Demonstrations},
  pages       = {38--45},
  year        = {2020},
  month       = {oct},
  publisher   = {Association for Computational Linguistics},
  address     = {Online},
  doi         = {10.18653/v1/2020.emnlp-demos.6},
  url         = {https://aclanthology.org/2020.emnlp-demos.6}
}

@article{Sokolova2009,
  author  = {Marina Sokolova and Guy Lapalme},
  title   = {A systematic analysis of performance measures for classification tasks},
  journal = {Information Processing \& Management},
  volume  = {45},
  number  = {4},
  pages   = {427--437},
  year    = {2009}
}


@misc{ModernBERT2024,
      title={Smarter, Better, Faster, Longer: A Modern Bidirectional Encoder for Fast, Memory Efficient, and Long Context Finetuning and Inference}, 
      author={Benjamin Warner and Antoine Chaffin and Benjamin Clavié and Orion Weller and Oskar Hallström and Said Taghadouini and Alexis Gallagher and Raja Biswas and Faisal Ladhak and Tom Aarsen and Nathan Cooper and Griffin Adams and Jeremy Howard and Iacopo Poli},
      year={2024},
      eprint={2412.13663},
      archivePrefix={arXiv},
      primaryClass={cs.CL},
      url={https://arxiv.org/abs/2412.13663}, 
}

@misc{LaurerZSC2023,
    title = {Building {Efficient} {Universal} {Classifiers} with {Natural} {Language} {Inference}},
    url = {http://arxiv.org/abs/2312.17543},
    doi = {10.48550/arXiv.2312.17543},
    abstract = {Generative Large Language Models (LLMs) have become the mainstream choice for fewshot and zeroshot learning thanks to the universality of text generation. Many users, however, do not need the broad capabilities of generative LLMs when they only want to automate a classification task. Smaller BERT-like models can also learn universal tasks, which allow them to do any text classification task without requiring fine-tuning (zeroshot classification) or to learn new tasks with only a few examples (fewshot), while being significantly more efficient than generative LLMs. This paper (1) explains how Natural Language Inference (NLI) can be used as a universal classification task that follows similar principles as instruction fine-tuning of generative LLMs, (2) provides a step-by-step guide with reusable Jupyter notebooks for building a universal classifier, and (3) shares the resulting universal classifier that is trained on 33 datasets with 389 diverse classes. Parts of the code we share has been used to train our older zeroshot classifiers that have been downloaded more than 55 million times via the Hugging Face Hub as of December 2023. Our new classifier improves zeroshot performance by 9.4\%.},
    urldate = {2024-01-05},
    publisher = {arXiv},
    author = {Laurer, Moritz and van Atteveldt, Wouter and Casas, Andreu and Welbers, Kasper},
    month = dec,
    year = {2023},
    note = {arXiv:2312.17543 [cs]},
    keywords = {Computer Science - Artificial Intelligence, Computer Science - Computation and Language},
}

@inproceedings{GELU2016,
  title     = {Gaussian Error Linear Units (GELUs)},
  author    = {Dan Hendrycks and Kevin Gimpel},
  year      = {2016},
  eprint    = {arXiv:1606.08415v3},
  eprinttype= {arXiv},
  eprintclass= {cs.LG},
  abstract  = {We propose the Gaussian Error Linear Unit (GELU), a high‑performing neural network activation function. The GELU nonlinearity weights inputs by their magnitude, rather than gates inputs by their sign as in ReLUs. We perform an empirical evaluation of the GELU nonlinearity against the ReLU and ELU activations and find performance improvements across all considered computer vision, natural language processing, and speech tasks.}
}

@inproceedings{Nie2020ANLI,
  author    = {Yixin Nie and Adina Williams and Emily Dinan and Mohit Bansal
               and Jason Weston and Douwe Kiela},
  title     = {Adversarial {NLI}: A New Benchmark for Natural Language Understanding},
  booktitle = {Proceedings of ACL},
  pages     = {4885--4901},
  year      = {2020}
}

@inproceedings{Liu2022WANLI,
  author    = {Alisa Liu and Swabha Swayamdipta and Noah A.~Smith and Yejin Choi},
  title     = {{WANLI}: Worker and {AI} Collaboration for Natural Language Inference Dataset Creation},
  booktitle = {Findings of EMNLP},
  pages     = {7080--7097},
  year      = {2022}
}

@inproceedings{Thorne2018FEVER,
  author    = {James Thorne and Andreas Vlachos and Christos Christodoulopoulos
               and Arpit Mittal},
  title     = {{FEVER}: A Large-scale Dataset for Fact Extraction and {VER}ification},
  booktitle = {Proceedings of NAACL--HLT},
  pages     = {809--819},
  year      = {2018}
}

@inproceedings{Parrish2021LingNLI,
  author    = {Alicia Parrish and William Huang and Omar Agha and Soo-Hwan Lee and
               Nikita Nangia and Alex Warstadt and Karmanya Aggarwal and Emily Allaway and
               Tal Linzen and Samuel R.~Bowman},
  title     = {Does Putting a Linguist in the Loop Improve {NLU} Data Collection?},
  booktitle = {Findings of EMNLP},
  pages     = {4886--4901},
  year      = {2021}
}


@inproceedings{Rashkin2019,
  title     = {Towards Empathetic Open-domain Conversation Models: A New Benchmark and Dataset},
  author    = {Hannah Rashkin and Eric Michael Smith and Margaret Li and Y-Lan Boureau},
  booktitle = {ACL},
  year      = {2019}
}

@inproceedings{Casanueva2020,
  title     = {Efficient Intent Detection with Dual Sentence Encoders},
  author    = {Iñigo Casanueva and Tadas Temcinas and Daniela Gerz and Matthew Henderson and Ivan Vulić},
  booktitle = {Proceedings of the 28th International Conference on Computational Linguistics},
  year      = {2020}
}

@inproceedings{Sap2020,
  title     = {Social Bias Frames: Reasoning about Social and Power Implications of Language},
  author    = {Maarten Sap and Saadia Gabriel and Lianhui Qin and Dan Jurafsky and Noah A. Smith and Yejin Choi},
  booktitle = {ACL},
  year      = {2020}
}

@inproceedings{Zhang2015,
  title     = {Character-level Convolutional Networks for Text Classification},
  author    = {Xiang Zhang and Junbo Zhao and Yann LeCun},
  booktitle = {NIPS},
  year      = {2015}
}

@article{Malo2014,
  title   = {Good Debt or Bad Debt: Detecting Semantic Orientations in Economic Texts},
  author  = {Pekka Malo and others},
  journal = {Journal of Emerging Technologies in Accounting},
  year    = {2014}
}

@inproceedings{Zhang2015Yelp,
  crossref = {Zhang2015},
  note     = {Yelp Reviews Polarity subset}
}

@inproceedings{Zhang2015Yahoo,
  crossref = {Zhang2015},
  note     = {Yahoo Answers Topics subset}
}

@inproceedings{Maas2011,
  title     = {Learning Word Vectors for Sentiment Analysis},
  author    = {Andrew L. Maas and Raymond E. Daly and Peter T. Pham and Dan Huang and Andrew Y. Ng and Christopher Potts},
  booktitle = {ACL},
  year      = {2011}
}

@inproceedings{Pang2005,
  title     = {Seeing Stars: Exploiting Class Relationships for Sentiment Categorization with Respect to Rating Scales},
  author    = {Bo Pang and Lillian Lee},
  booktitle = {ACL},
  year      = {2005}
}

@inproceedings{FitzGerald2022,
  title     = {MASSIVE: A 1M-Example Multilingual NLU Dataset with 51 Typologically-Diverse Languages},
  author    = {Jack FitzGerald and others},
  booktitle = {EMNLP},
  year      = {2022}
}

@inproceedings{Gekhman2023,
  title     = {TrueTeacher: Learning Factual Consistency Evaluation with Large Language Models},
  author    = {Ziv Gekhman and others},
  booktitle = {EMNLP},
  year      = {2023}
}

@inproceedings{Lehmann2024,
  title     = {The Manifesto Data Collection, Version 2024a},
  author    = {Pola Lehmann and Simon Franzmann and others},
  booktitle = {WZB Data Release},
  year      = {2024}
}

@inproceedings{Wulczyn2017,
  title     = {Ex Machina: Personal Attacks Seen at Scale},
  author    = {Ellery Wulczyn and Nithum Thain and Lucas Dixon},
  booktitle = {WWW},
  year      = {2017}
}

@inproceedings{Saravia2018,
  title     = {CARER: Contextualized Affect Representations for Emotion Recognition},
  author    = {Elvis Saravia and Hsien-Chi Toby Liu and Yen-Hao Huang and Junlin Wu and Yi-Shin Chen},
  booktitle = {Proceedings of EMNLP 2018},
  address   = {Brussels, Belgium},
  pages     = {3687--3697},
  doi       = {10.18653/v1/D18-1404},
  year      = {2018}
}

@inproceedings{Grano2017,
  title     = {Android Apps and User Feedback: A Dataset for Software Evolution and Quality Improvement},
  author    = {Giovanni Grano and Andrea Di Sorbo and Francesco Mercaldo and Corrado~A. Visaggio and Gerardo Canfora and Sebastiano Panichella},
  booktitle = {Proceedings of the 2nd ACM SIGSOFT International Workshop on App Market Analytics (WAMA)},
  pages     = {8--11},
  year      = {2017},
  doi       = {10.1145/3121264.3121266}
}

@misc{Jones2023SOTU,
  author       = {Bryan D. Jones and Frank R. Baumgartner and Sean M. Theriault and Derek A. Epp and Rebecca Eissler and Cheyenne Lee and Miranda E. Sullivan},
  title        = {Policy Agendas Project: State of the Union Speeches},
  year         = {2023},
  note         = {Comparative Agendas Project dataset},
  howpublished = {\url{https://www.comparativeagendas.net/}}
}