| Dataset Name | SOTA Method | Metric | Trend | ||
|---|---|---|---|---|---|
| Flowers102 | PromptKD | Base Accuracy99.42 | 29 | 4d ago | |
| SUN397 | PromptKD + MERGETUNE | Base Score83.92 | 27 | 4d ago | |
| EuroSAT | PromptKD + MERGETUNE | Base Score97.81 | 26 | 4d ago | |
| ImageNet base-to-novel | PromptKD + MERGETUNE | Base Score80.89 | 22 | 4d ago | |
| Food 101 | PromptKD + MERGETUNE | Base Score92.45 | 19 | 4d ago | |
| Average base-to-novel | MMRL | Base Score0.8568 | 13 | 4d ago | |
| Oxford Flowers | 2SFSLayerNorm | Base Accuracy98.29 | 13 | 4d ago | |
| StanfordCars (test) | MMRL++ | Base Accuracy81.33 | 12 | 4d ago | |
| Average (K-400, HMDB-51, UCF-101, SSv2) | FROSTER | Top-1 Acc (Base)66.4 | 9 | 4d ago | |
| SS v2 | FROSTER | Top-1 Acc (Base)18.3 | 9 | 4d ago | |
| K-400 | TC-CLIP | Top-1 Acc (Base)79.1 | 9 | 4d ago | |
| Biomedical datasets Average | BiomedCoOp | Base Accuracy76.26 | 6 | 4d ago | |
| UCF101 base-to-novel | MMRL | Base Score88.1 | 4 | 4d ago |
