Federated Continual Learning on ImageNet R
87.2Avg Accuracy
C²Prompt
Updated 1mo ago
Evaluation Results
| Method | Links | ||||||
|---|---|---|---|---|---|---|---|
2025.09 | 87.2 | 85.93 | -0.36 | 7.63 | 1.12 | 8.52 | |
2025.09 | 84.69 | 84.08 | -0.54 | 4.48 | 1.95 | 6.04 | |
2025.09 | 79.65 | 75.14 | -0.68 | -2.53 | 1.69 | -1.18 | |
2025.09 | 77.88 | 75.03 | 0.41 | -2.79 | -0.17 | -2.92 | |
2025.09 | 76.85 | 74.91 | 0.49 | -3.12 | 0.22 | -2.95 | |
2025.09 | 76.75 | 72.59 | 0.63 | -3.16 | 0 | -3.16 | |
2025.09 | 72.96 | 75.21 | 1.1 | -3.87 | -1.55 | -5.11 | |
2025.09 | 72.27 | 73.36 | 2.01 | -2.6 | -4.91 | -5.95 | |
2025.09 | 71.1 | 74.3 | 1.8 | -2.39 | -1.83 | -3.86 | |
2025.09 | 58 | 67.78 | 8.71 | -4.67 | -9.22 | -13.7 | |
2025.09 | 47.93 | 59.79 | 3.81 | -17.67 | -14.92 | -29.6 | |
2025.09 | 47.67 | 47.08 | 1.4 | -3.3 | -0.12 | -3.37 | |
2025.09 | 45.43 | 48.72 | 0.92 | -5.75 | -7.32 | -12.54 |