| Task Name | Dataset Name | SOTA Result | Trend | |
|---|---|---|---|---|
| Image Classification | FGVCAircraft | Accuracy94.16 | 225 | |
| Base-to-New Generalization | FGVCAircraft | Base Performance51.58 | 64 | |
| Fine-Grained Visual Categorization | FGVCAircraft | Accuracy95.6 | 60 | |
| Fine-grained Image Classification | FGVCAircraft (novel classes) | ECE3.79 | 36 | |
| Classification | FGVCAircraft | Robust Accuracy32.5 | 30 | |
| Fine-grained classification | FGVCAircraft (base classes) | Accuracy42 | 27 | |
| Fine-grained classification | FGVCAircraft Base-to-New | Base Accuracy42.68 | 23 | |
| Image Classification | FGVCAircraft H (harmonic mean) | Acc42.78 | 16 | |
| Fine-grained classification | FGVCAircraft (novel classes) | MCE0.88 | 15 | |
| Zero-shot Classification | FGVCAircraft | Top-1 Clean Acc23.8 | 10 | |
| Exemplar-Free Class-Incremental Learning | FGVCAircraft T=20 tasks (test) | Last Accuracy34.8 | 9 | |
| Exemplar-Free Class-Incremental Learning | FGVCAircraft T=10 tasks (test) | Last Accuracy (Alast)47.5 | 9 | |
| Exemplar-Free Class-Incremental Learning | FGVCAircraft T=5 tasks (test) | Last Accuracy53.3 | 9 | |
| Image Classification | FGVCAircraft | Accuracy (1 Shot)33.75 | 6 | |
| Few-Shot Class-Incremental Image-to-Text | FGVCAircraft | Accuracy18.98 | 6 | |
| Unseen prompt generalization | FGVCAircraft | Accuracy36.29 | 6 | |
| Image Recognition | FGVCAircraft | Natural Accuracy19.2 | 5 | |
| Image Classification | FGVCAircraft (unseen) | Accuracy36.29 | 4 | |
| Image Classification | FGVCAircraft (seen) | Accuracy40.44 | 4 | |
| Image Classification | FGVCAircraft (10% labels) | Top-1 Acc57.1 | 3 | |
| Image Classification | FGVCAircraft (val) | Accuracy- | 0 |