ReCalCon

Checkpoints for Re-calibrated Contrastive Loss for Transformation-Aware Prompt Conditioning in Vision-Language Models (BMVC 2026). Paper ยท Code

Each folder holds model.safetensors (the full model state dict, fp32) and config.json, which names the released config to evaluate it with.

Usage

hf download SoongE/ReCalCon --include "distribution_shift/imagenet_b16/*" --local-dir checkpoints
python -m scripts.eval --config imagenet_b16 \
  --eval.checkpoint checkpoints/distribution_shift/imagenet_b16/model.safetensors

Checkpoints

Distribution shift (top-1 accuracy, %)

Checkpoint Row ImageNet -R -A -V2 -Sketch ObjectNet
distribution_shift/imagenet_b16 ViT-B/16, Update, ImageNet 83.284 71.607 54.893 74.1 51.781 58.388
distribution_shift/imagenet_b32 ViT-B/32, Update, ImageNet 79.354 62.41 32.573 68.15 44.503 49.203
distribution_shift/imagenet_petl_b16 ViT-B/16, Freeze (PETL), ImageNet 80.206 73.163 50.867 70.13 49.614 55.691
distribution_shift/imagenet_petl_b32 ViT-B/32, Freeze (PETL), ImageNet 76.12 63.563 30.453 64.52 42.267 46.662

iWildCam (macro-F1, %). The released evaluation reports the OOD split.

Checkpoint Row ID (macro-F1) OOD (macro-F1)
distribution_shift/iwildcam_b16 ViT-B/16, Update, iWildCam 51.253 37.803
distribution_shift/iwildcam_b32 ViT-B/32, Update, iWildCam 42.116 29.275
distribution_shift/iwildcam_petl_b16 ViT-B/16, Freeze (PETL), iWildCam 45.49 30.327
distribution_shift/iwildcam_petl_b32 ViT-B/32, Freeze (PETL), iWildCam 34.709 24.502

Transfer learning (top-1 accuracy, %)

Checkpoint Dataset Accuracy
transfer/caltech101 Caltech101 97.85
transfer/flowers102 Flowers102 98.894
transfer/pcam PCam 89.413
transfer/stanfordcars StanfordCars 91.419

License

Apache License 2.0. The models are fine-tuned from OpenAI CLIP (MIT License); each evaluation dataset keeps its own terms.

Citation

@inproceedings{oh2026recalibrated,
  title     = {Re-calibrated Contrastive Loss for Transformation-Aware Prompt Conditioning in Vision-Language Models},
  author    = {Oh, Seungmin and Kang, Seunghun and Ryu, Jongbin},
  booktitle = {Proceedings of the British Machine Vision Conference},
  year      = {2026},
  publisher = {BMVA},
  url       = {https://arxiv.org/abs/2609.06967}
}
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