| Dataset Name | SOTA Method | Metric | Trend | ||
|---|---|---|---|---|---|
| CIFAR-10 | Randomized Input Defense | Clean Accuracy95.32 | 68 | 1mo ago | |
| CIFAR-10-C common corruptions (test) | CCAT | Accuracy (Snow)89.38 | 16 | 1mo ago | |
| CIFAR-10 (test) | Diff-BPDA | Classification Accuracy92.19 | 12 | 1mo ago | |
| RobustBench (test) | Stutz et al. | RA90 | 12 | 1mo ago | |
| CIFAR-100 RobustBench standard (val) | IKL-KD | Clean Accuracy73.85 | 6 | 1mo ago | |
| FashionMNIST (test) | A5/RC | Error11.41 | 5 | 1mo ago | |
| ImageNet-1K | TGA-ZSR | Robust Accuracy2.51 | 4 | 1mo ago | |
| Caltech-256 | SAFT-L | Robust Accuracy19.15 | 4 | 1mo ago | |
| Food101 | TGA-ZSR | Robust Accuracy213 | 4 | 1mo ago | |
| Tiny-ImageNet | TGA-ZSR | Robust Accuracy16.76 | 4 | 1mo ago | |
| 15 Datasets Aggregate Zero-shot | SAFT-L | Zero-shot Robust Accuracy8.65 | 4 | 1mo ago | |
| FGVC-Aircraft | PMG-AFT | Robust Accuracy6 | 4 | 1mo ago | |
| DTD | - | Robust Accuracy- | 0 | 1mo ago | |
| Flowers102 | - | Robust Accuracy- | 0 | 1mo ago | |
| STL-10 | - | Robust Accuracy- | 0 | 1mo ago | |
| CIFAR-10, CIFAR-100, and TinyImageNet Overall (test) | - | - | 0 | 1mo ago | |
| MNIST (test) | - | - | 0 | 1mo ago |
