ResNet18/MART-ANCRA

Reported on 2 benchmarks across 1 task · 1 paper

Note: results are matched by exact model name. Different papers may use the same name for different model variants.

Adversarial2 results

Adversarial RobustnessonCIFAR-100
AutoAttacked Accuracy· 2023-10-05
35.05
best: 38.72 (Mixed Classifier)
Enhancing Robust Representation in Adversarial Training: Alignment and Exclusion Criteria arXiv:2310.03358
Adversarial RobustnessonCIFAR-100
Clean Accuracy· 2023-10-05
60.1
best: 85.21 (Mixed Classifier)
Enhancing Robust Representation in Adversarial Training: Alignment and Exclusion Criteria arXiv:2310.03358