| Dataset Name | SOTA Method | Metric | Trend | ||
|---|---|---|---|---|---|
| CIFAR-100 | SGDS | Averaged Incremental Accuracy94.98 | 234 | 2d ago | |
| ImageNet-R | Average Accuracy94.6 | 103 | 2d ago | ||
| ImageNet-A | SGDS | Average Accuracy74.39 | 86 | 2d ago | |
| CIFAR100 (test) | TagFex | Avg Acc78.45 | 76 | 3d ago | |
| CIFAR-100 Split (test) | NoRGa | Avg Acc94.76 | 75 | 3d ago | |
| CIFAR-100 10 (test) | RanPAC | Average Top-1 Accuracy92.2 | 75 | 2d ago | |
| ImageNet-100 | Ours | Avg Acc87.76 | 74 | 3d ago | |
| CIFAR100 B50 (test) | Average Accuracy79.91 | 67 | 3d ago | ||
| CIFAR-100 | RanPAC | Average Accuracy92.4 | 60 | 3d ago | |
| CIFAR10 (test) | Average Accuracy92.2 | 59 | 3d ago | ||
| Split ImageNet-R | Average Forgetting Measure1.27 | 57 | 3d ago | ||
| Food101-LT rho=100 (test) | Ours | Accuracy36.84 | 48 | 3d ago | |
| ImageNet Subset-LT rho=100 (test) | Ours | Accuracy50.57 | 48 | 3d ago | |
| CIFAR100-LT rho=100 (test) | FOSTER-2stage | Avg Acc40.26 | 48 | 3d ago | |
| CUB | RanPAC | Avg Accuracy90.6 | 45 | 2d ago | |
| ImageNet-R 10-task | FAA82.06 | 44 | 3d ago | ||
| ImageNet-100 B=50, C=10 1.0 | DER w/ C-Flat | Avg Incremental Acc86.64 | 42 | 2d ago | |
| Split CIFAR-100 (10-task) | HiDe-Prompt | CAA95.02 | 41 | 3d ago | |
| ObjectNet | Average Accuracy83.8 | 40 | 3d ago | ||
| CIFAR100-B0 (test) | DER | Accuracy76.8 | 40 | 3d ago | |
| CIFAR-10 Sequential | FAA98.25 | 39 | 3d ago | ||
| CUB200 | Last Accuracy89.23 | 39 | 3d ago | ||
| Stanford Cars (test) | ADC | Accuracy (Last)54.86 | 38 | 3d ago | |
| CUB-200 (test) | ADC | Alast64.46 | 38 | 3d ago | |
| CIFAR-100 B0_Inc5 | TOSCA | Average Accuracy96.37 | 36 | 3d ago |
