| Task Name | Dataset Name | SOTA Result | Trend | |
|---|---|---|---|---|
| Image Classification | CIFAR100 (test) | Top-1 Accuracy93.4 | 377 | |
| Image Classification | CIFAR100 long-tailed (test) | Accuracy66.3 | 155 | |
| Image classification | CIFAR100 (test) | Accuracy56.19 | 112 | |
| Clustering | CIFAR100 20 | ACC61.4 | 93 | |
| Continual Learning | CIFAR100 Split | Average Per-Task Accuracy95.38 | 85 | |
| Class Incremental Learning | CIFAR100 (test) | Avg Acc78.45 | 76 | |
| Image Classification | CIFAR100 IDN (test) | Accuracy79.69 | 67 | |
| Class Incremental Learning | CIFAR100 B50 (test) | Average Accuracy79.91 | 67 | |
| Continual Learning | CIFAR100 Split 32x32 (test) | Accuracy30.1 | 66 | |
| Image Classification | CIFAR100 UnLabel-Domain (UL) | Accuracy61.8 | 52 | |
| Image Classification | CIFAR100 Labeled-Domain (L) | Accuracy76.4 | 52 | |
| Image Classification | CIFAR100 10 tasks (test) | Accuracy49.7 | 51 | |
| Continual Learning | CIFAR100 10 tasks (test) | Average Forgetting Rate5.6 | 51 | |
| Image Classification | CIFAR100 (test) | Error Rate19.01 | 49 | |
| Class-Incremental Learning | CIFAR100-LT rho=100 (test) | Avg Acc40.26 | 48 | |
| Semi-supervised Image Classification | CIFAR100-LT (test) | Accuracy0.613 | 48 | |
| Partial Label Learning | CIFAR100-LT | Accuracy64.75 | 48 | |
| Out-of-Distribution Detection | CIFAR100 ID Dnear OOD | AUROC81.37 | 47 | |
| Image Classification | CIFAR100-LT (test) | Top-1 Acc (IR=100)59.59 | 45 | |
| Image Classification | CIFAR100 without Cutout (test) | Accuracy79.71 | 45 | |
| OOD Detection | CIFAR100-C all 15 perturbations (test) | AUROC69.69 | 43 | |
| Image Classification | CIFAR100 (test) | Accuracy92.21 | 43 | |
| Binary Classification | Binary CIFAR100 (imbalance ratio 1:100) (test) | FPR @ 98% TPR64 | 41 | |
| Image Classification | CIFAR100 Clean (test) | Accuracy83.09 | 38 | |
| Membership Inference Attack | CIFAR100 (test) | AUC0.99 | 37 |