| Dataset Name | SOTA Method | Metric | Trend | ||
|---|---|---|---|---|---|
| Aircraft | CAP | Top-1 Acc94.9 | 62 | 3d ago | |
| EuroSAT | TTC | Accuracy64.1 | 57 | 2d ago | |
| Stanford Cars | MMAL-Net | Accuracy95 | 31 | 2d ago | |
| Food101 | CAP | Accuracy98.6 | 30 | 2d ago | |
| UCF101 | C-TPT | Accuracy75.1 | 29 | 2d ago | |
| Caltech101 | TPT | Accuracy95.9 | 29 | 2d ago | |
| SUN397 (novel classes) | TCPT | ECE0.77 | 28 | 2d ago | |
| EuroSAT (novel classes) | DAC | Expected Calibration Error3.33 | 28 | 2d ago | |
| UCF101 (base classes) | TCPT | Accuracy84.68 | 27 | 2d ago | |
| EuroSAT base classes | Temp. Scal. | Accuracy93.6 | 27 | 2d ago | |
| DTD (base classes) | ZS-Norm | Accuracy81.02 | 27 | 2d ago | |
| SUN397 (base classes) | TCPT | Accuracy81.68 | 27 | 2d ago | |
| FGVCAircraft (base classes) | Temp. Scal. | Accuracy42 | 27 | 2d ago | |
| Food101 (base classes) | ZS-Norm | Accuracy91.71 | 27 | 2d ago | |
| OxfordPets (base classes) | ZS-Norm | Accuracy97.65 | 27 | 2d ago | |
| Caltech101 (base classes) | MBLS | Accuracy98.23 | 27 | 2d ago | |
| Flower102 (test) | Accuracy97.8 | 27 | 3d ago | ||
| SUN397 | CLIP | Top-1 Accuracy78.4 | 25 | 2d ago | |
| FGVC Aircraft | ResNet-50 (ReLabel-trained) | Accuracy88.89 | 25 | 2d ago | |
| DTD | R-TPT | Clean Accuracy54 | 24 | 2d ago | |
| iNaturalist-19 | HiE | Top-1 Error Rate35.33 | 24 | 2d ago | |
| FGVCAircraft Base-to-New | HPT | Base Accuracy42.68 | 23 | 3d ago | |
| Describable Textures Dataset (DTD) | C-TPT | Accuracy55.4 | 23 | 2d ago | |
| ImageNet (novel classes) | Penalty | ECE1.49 | 22 | 2d ago | |
| Pets | CLIP | Accuracy88.25 | 22 | 3d ago |
