| Dataset Name | SOTA Method | Metric | Trend | ||
|---|---|---|---|---|---|
| EuroSAT | TTC | Accuracy64.1 | 138 | 1mo ago | |
| Aircraft | CAP | Top-1 Acc94.9 | 105 | 26d ago | |
| UCF101 | C-TPT | Accuracy75.1 | 98 | 1mo ago | |
| Stanford Cars | MMAL-Net | Accuracy95 | 96 | 1mo ago | |
| Caltech101 | TPT | Accuracy95.9 | 76 | 1mo ago | |
| Pets | MTA | Accuracy93.7 | 58 | 1mo ago | |
| DTD | R-TPT | Clean Accuracy54 | 54 | 1mo ago | |
| Cars | w/ LaViD | Accuracy91.66 | 54 | 26d ago | |
| Food101 | SigLIP2-B/16-256 | Top-1 Acc94.7 | 52 | 2mo ago | |
| FGVC Aircraft | ResNet-50 (ReLabel-trained) | Accuracy88.89 | 51 | 1mo ago | |
| Cars | MTA | Accuracy78.4 | 42 | 1mo ago | |
| Pets (test) | MTA | Accuracy85.9 | 42 | 1mo ago | |
| Oxford Flowers 102 | DINOv3-B | Accuracy99.69 | 41 | 2mo ago | |
| Flower102 (test) | Accuracy97.8 | 40 | 1mo ago | ||
| SUN397 | CLIP | Top-1 Accuracy78.4 | 39 | 4mo ago | |
| Flower102 | TTC | Clean Accuracy76.5 | 38 | 1mo ago | |
| DTD | LoRA | Accuracy86.58 | 38 | 1mo ago | |
| Describable Textures Dataset (DTD) | C-TPT | Accuracy55.4 | 37 | 2mo ago | |
| Oxford-IIIT Pets | OmniVec2 | Top-1 Accuracy99.6 | 37 | 2mo ago | |
| Aircraft | MTA | Accuracy32.7 | 35 | 1mo ago | |
| Pets | w/ LaViD | Top-1 Accuracy85.79 | 33 | 26d ago | |
| Caltech | w/ LaViD | Top-1 Accuracy85.01 | 33 | 26d ago | |
| Aircraft | MTA | Clean Accuracy25 | 31 | 1mo ago | |
| Cars | MTA | Clean Accuracy67.7 | 31 | 1mo ago | |
| Pets | CLIP | Clean Accuracy88.3 | 31 | 1mo ago |
