Class-Incremental Learning on CIFAR-100 and ImageNet-A benchmark leaderboard · SOTA2 Research

Class-Incremental Learning on CIFAR-100 and ImageNet-A

88.32Accuracy (Last Task)One-A

Evaluation Results

Method	Links
One-A2026.03		88.32	92.54
EASE2026.03		87.52	91.98
EASE2026.03		87.02	91.74
One-A2026.03		86.83	91.46
Aper-adapter2026.03		86.32	90.34
One-A2026.03		86.27	90.78
ACMap2026.03		85.81	91.21
SEMA2026.03		85.63	91.18
Aper-adapter2026.03		84.91	90.31
EASE2026.03		84.79	90.42
SEMA2026.03		84.7	88.58
One-A2026.03		84.68	89.58
EASE2026.03		84.42	89.23
ACMap2026.03		84.25	89.08
CL-LoRA2026.03		83.96	89.79
ACMap2026.03		83.8	88.84
ACMap2026.03		83.43	90.15
Aper-adapter2026.03		83.05	88.32
Aper-adapter2026.03		82.41	87.68
CL-LoRA2026.03		82.34	89.98
SEMA2026.03		81.48	87.85
CL-LoRA2026.03		80.43	89.44
CL-LoRA2026.03		76.76	84.39
SEMA2026.03		74.85	81.86