| --- |
| license: apache-2.0 |
| --- |
| |
| # angular-separation-vit — reproduction checkpoints |
|
|
| Final (`_last.pt`) checkpoints backing *"Dos modelos idénticos, dos |
| podas distintas: la dirección dominante de $W_O$ bajo intervención |
| libre, suave y dura"* ("Same function, different pruning: the |
| dominant direction of $W_O$ under free, soft, and hard intervention"). |
| These are verification artifacts for reproducing the paper's tables — |
| not meant as general-purpose pretrained weights. |
| |
| Code: <https://github.com/mmunozpl/angular-separation-vit> |
| CSV results derived from these checkpoints: <https://huggingface.co/datasets/ManuelPla/angular-separation-vit-results> |
| |
| ## Layout |
| |
| ``` |
| vitb_clean/attnA_{base,blanda,dura}_seed{42..46}_last.pt # ancla, n=5 |
| vitl_clean/attnA_{base,blanda,dura}_seed{42..44}_last.pt # n=3 |
| dinov2_clean/attnA_base_seed42_last.pt # frozen, n=1 |
| ``` |
| |
| `base` = fine-tuned ViT with no angular regularizer. `blanda` = soft |
| angular probe (`R_div`, eq. 5). `dura` = hard variant, reprojected to |
| the spherical code after every optimizer step. DINOv2 is analyzed |
| frozen (no fine-tuning), hence a single realization. |
|
|
| All backbones derive from `timm` pretrained weights (ImageNet-1k for |
| ViT-B/16 and ViT-L/16; LVD-142M self-supervised pretraining for |
| DINOv2), fine-tuned on ImageNet-100 for the two supervised columns. |
| Redistributed under Apache-2.0, consistent with the code license; |
| verify compatibility with upstream pretraining licenses before reuse |
| beyond reproduction of this paper. |
|
|
| ## License |
|
|
| Apache-2.0. |
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|
