| Dataset Name | SOTA Method | Metric | Trend | ||
|---|---|---|---|---|---|
| CIFAR-10 | Retain Accuracy100 | 66 | 1mo ago | ||
| CIFAR-10 (test) | FT | Test Accuracy94.78 | 42 | 2mo ago | |
| CIFAR-10 | SalUn | PUL99.35 | 40 | 4mo ago | |
| CIFAR-10 | MIA Accuracy (Mean)100 | 32 | 2mo ago | ||
| CIFAR-10 | Retain Accuracy97.22 | 28 | 2mo ago | ||
| Lacuna 10 (test) | CF-k | Test Error (Mean)1.48 | 27 | 4mo ago | |
| Lacuna-10 | Test Error1.67 | 27 | 4mo ago | ||
| CIFAR-10 | NegGrad | Training Time (s)10.87 | 24 | 2mo ago | |
| CIFAR-100 (test) | Acc (Dr)80.71 | 22 | 3mo ago | ||
| Tiny-ImageNet (test) | Df (Degree of Forgetting)96.72 | 19 | 4mo ago | ||
| CIFAR-10 | Test Error13.98 | 18 | 4mo ago | ||
| FASHION-MNIST | BadT | MIA Rate0 | 14 | 2mo ago | |
| Small CIFAR-5 | CF-k | Retention Accuracy99.96 | 13 | 4mo ago | |
| CIFAR-10 | l1 | U-LiRA Accuracy98.32 | 12 | 4mo ago | |
| CIFAR100 | MIA Success Rate (No Attack)2.4 | 10 | 1mo ago | ||
| Text Generation Dataset | Residual Feature Alignment | Forgetting Rate (Dr)0.39 | 10 | 2mo ago | |
| CIFAR-100 | SSD | Average Gap0.4325 | 10 | 4mo ago | |
| TinyImageNet (TinyIN) | Average Gap0 | 10 | 4mo ago | ||
| CIFAR-20 superclass (veg) | SSD | Dr (Utility)95.71 | 8 | 1mo ago | |
| CIFAR-20 Veh2 superclass | Retention (Dr)95.73 | 8 | 1mo ago | ||
| Tiny-ImageNet | Total Accuracy (TA)64.17 | 7 | 1mo ago | ||
| CIFAR10 | Target Accuracy (TA)94.14 | 7 | 1mo ago | ||
| CIFAR-100 forget (Class-0) | Forget Error0 | 7 | 4mo ago | ||
| CIFAR-100 retain (train) | Retain Error0.07 | 7 | 4mo ago | ||
| CIFAR-10 | NegGrad | Dr2.76 | 6 | 2mo ago |
