ACTok ResNet-50 and ConvNeXt-B checkpoints (PCA validated)

PCA-validated CNN checkpoints

These checkpoints were checked against historical project figures before release. All compared outputs use backbone features, not aggregation-head outputs. Strict loading and finite CPU inference were checked; benchmark scores were not reproduced.

File	Contents / teachers	Size	Historical PCA agreement
resnet_distill.pth	ResNet-50 backbone only	90.0 MiB	0.99997 mean raw RGB correlation vs. historical oranges PCA
convnext_b_norm_distill.pth	ConvNeXt-B, CNN teachers; backbone + aggregation modules	370.8 MiB	0.99780 vs. Figure 6(b)'s embedded JPEG
convnext_b_norm_distill_allvit.pth	ConvNeXt-B, ViT teachers; backbone + aggregation modules	364.6 MiB	0.9999999 vs. visualizations/fern.png, also Figure 6(c)

PCA comparisons use the historical OpenAI normalization, resize/crop settings, and no RGB sign/channel/color adjustments. The images are near-matches rather than pixel-exact: JPEG and plotting differences remain. The old ResNet run uses whitened linear PCA at 3072×3072; the ConvNeXt runs use cosine-kernel PCA at 4096×4096.

See the README and tools/validate_checkpoint_pca.py for strict backbone loading and reproduction commands. The ConvNeXt files contain extra aggregation modules, but the validated representation uses the student.* state. The published configuration and validation JSON assets include details. Verify downloaded files with CNN_SHA256SUMS.

Excluded: the _l2 ConvNeXt experiment did not reproduce the selected reference; resnet_distill_student.pth has no prediction heads and differs from the validated backbone. A distilled ViT-L student checkpoint was not found locally, so no ViT-L model is included.