## Supplementary Code for ICLR 2026 Reviwers

We provide a small sample of our results for reviewers to interact with --- please feel free to inspect the meshes provided to help build intuition of extracted features. Unfortunately, due to size constraints, we are unable to provide a significant library of models. We hope that you find the sample sufficient to validate our printed results.

### ablation_figures.py

We provide a subset (~85k) of the ablations discussed in Sections 4 and 5 of our paper. 

This file contains all the necessary methods to produce our figures for the paper, as well as the helper methods to interact with the data. We recommend initializing the code as such:
```
from ablation_figures import *
ablations, values, densities = get_ablations_from_pickle()
all_ablations, all_values, all_densities = stack_all_ablations()
```

From here, all figure functions take one or more of these variables. Again, due to size constraints, we are only able to provide a subset of the data, so exact reproductions are not possible, and certain trends may be more difficult to confirm. 

### mesh_figures.py

We provide an example mesh, alongside an ablation and addition as described in the paper. We also provide all helper functions to inspect these meshes. We recommend initializing code as such:

```
from mesh_figures import *
mesh, cloud = prep_mesh_and_cloud('meshes/simple_garden.glb', 'meshes/test_352.ply', reflection=[1, -1, -1])
```

From here, you may use open3d's ``draw_geometries`` function to visualize the mesh and cloud together, or if you prefer, you may use our rendering code.

```
render_transparent_mesh_with_points(mesh, cloud, -60, 70, -30, 50, camera_offset=[-250, 0, 0], skip_pcd=True, up=[0, 1, 0], mesh_alpha=1)
```

Files in `meshes` prepended with `test_` are examinations of features, as in Figure 2 of our paper. They are viewable as point clouds. Each `test_` file was taken from features that fired on over a certain threshold of latents in the model.

We also provide some of the modified models shown in Figure 3 of our paper. We present the result of the ablation of feature 363 and addition of feature 452, as well a full and partial ablation of feature 313. To prepare these models, run:

```
mesh, cloud = prep_mesh_and_cloud('meshes/template_add_363_426.ply', 'meshes/test_363.ply', reflection=[1, 1, 1])
```
substituting `meshes/template_add_363_426.ply` with the desired mesh.

Again, you may view it through ```draw_geometries``` or our rendering code.
```
render_transparent_mesh_with_points(mesh, cloud, -1.1, 1, -0.5, 1, camera_offset=[-250, 0, 0], skip_pcd=True, up=[0, 1, 0], mesh_alpha=1)
```