Class-Incremental Learning on CIFAR100 rho=0.1 (test)
77.3Alast AccuracySL-Tree
Evaluation results
| Method | Links | ||
|---|---|---|---|
| SL-TreeBackbone=ViT-B/162026.03 | 77.3 | 1.3 | |
| MG-CLIP2026.03 | 75.6 | 1.7 | |
| RAPF2026.03 | 75.4 | 1.9 | |
| GMM2026.03 | 74.5 | 2.1 | |
| CODAPrompt2026.03 | 74.4 | 1.6 | |
| APART2026.03 | 74.3 | 1.5 | |
| DAP2026.03 | 74 | 2.1 | |
| SL-TreeBackbone=ViT-B/162026.03 | 72 | 1.2 | |
| MG-CLIP2026.03 | 71.3 | 1.8 | |
| APART2026.03 | 71 | 1.4 | |
| RAPF2026.03 | 70.9 | 1.9 | |
| DAP2026.03 | 70.8 | 2.1 | |
| GMM2026.03 | 70.2 | 2.1 | |
| CODAPrompt2026.03 | 69.2 | 1.9 | |
| DualPrompt2026.03 | 68.2 | 1.8 | |
| L2P2026.03 | 67.5 | 2 | |
| PriViLege2026.03 | 66.6 | 2.3 | |
| L2P2026.03 | 61.3 | 2.5 | |
| DualPrompt2026.03 | 61.3 | 2 | |
| PriViLege2026.03 | 60.4 | 2.1 | |
| ISPC2026.03 | 53.4 | 4.1 | |
| PODNET + GVAlign2026.03 | 53 | 4.7 | |
| ISPC2026.03 | 52.4 | 3.8 | |
| PODNET + LWS2026.03 | 51.9 | 5.1 | |
| PODNET + GVAlign2026.03 | 51.9 | 4 | |
| PODNET + LWS2026.03 | 51 | 4.3 | |
| LFM+MMS2026.03 | 39.7 | 22.6 | |
| LFM+MMS2026.03 | 27.4 | 25.7 |