| Dataset Name | SOTA Method | Metric | Trend | ||
|---|---|---|---|---|---|
| TOFU (5%) | OPT-OUT | Forget Quality86.6 | 59 | 4d ago | |
| Tiny-ImageNet 20 classes | Retain-only Retrain | Retain Accuracy66.38 | 48 | 8d ago | |
| CIFAR-100 10 classes | Retain-only Retrain | Retain Accuracy76.5 | 48 | 8d ago | |
| CIFAR-100 1 class | Retain-only Retrain | Retain Accuracy76.01 | 48 | 8d ago | |
| CIFAR-10 3 classes | Retain-only Retrain | Retain Accuracy95.37 | 48 | 8d ago | |
| CIFAR-10 1 class | Retain-only Retrain | Retain Accuracy94.74 | 48 | 8d ago | |
| Tiny-ImageNet 1 class (forget) | Retain-only Retrain | Retain Accuracy66.52 | 48 | 8d ago | |
| TOFU Forget01 (1% authors) | Original | Forget Quality (Rouge-L)0.99 | 48 | 1mo ago | |
| CIFAR-100 | NegGrad + SAM 0.1 | ToW (High)82.86 | 48 | 1mo ago | |
| ImageNette gas pump Class 7 (test) | SalUn | Forget Accuracy100 | 48 | 1mo ago | |
| CIFAR-10 bird, Class 2 (test) | Forgetting Accuracy (Class)100 | 48 | 1mo ago | ||
| CIFAR-10 | Accf99.94 | 45 | 1mo ago | ||
| CIFAR-100 (test) | MaGA | Retain Acc92.34 | 45 | 19d ago | |
| MNIST | Model Accuracy98.22 | 44 | 1mo ago | ||
| Tiny-ImageNet (train) | Forgetting Accuracy (Train)99.9 | 43 | 19d ago | ||
| TOFU | Forget Quality (FQ)1 | 43 | 1mo ago | ||
| TOFU Forget10 (10% authors split) | Original | Forget Quality - Rouge-L0.99 | 42 | 1mo ago | |
| TOFU Forget05 (5% authors) | Original | Forget Quality (ROUGE-L)0.99 | 42 | 1mo ago | |
| CIFAR-100 In Class Random Forgetting | RA (Utility Retention)99.98 | 40 | 4d ago | ||
| RWKU Llama 3.1 8B (Forget Set) | FB Score85.9 | 39 | 1mo ago | ||
| TOFU (10%) | Retain LLM | Forget Quality (FQ)1 | 37 | 4d ago | |
| CIFAR-100 (forget set) | SharpMinMax | Avg Increase in Forget Accuracy18.511 | 36 | 1mo ago | |
| TOFU (1%) | ECO | Forget Quality (FQ)0.0002 | 36 | 4d ago | |
| MUSE Books | PDU | Privacy Leakage-76.1834 | 35 | 18d ago | |
| TOFU 1.0 (forget01) | ME_KL | MU Score78.88 | 33 | 1mo ago |
