Catastrophic Overfitting: A Potential Blessing in Disguise

arXiv:2402.18211v1 Announce Type: new
Abstract: Fast Adversarial Training (FAT) has gained increasing attention within the research community owing to its efficacy in improving adversarial robustness. Particularly noteworthy is the challenge posed by catastrophic overfitting (CO) in this field. Although existing FAT approaches have made strides in mitigating CO, the ascent of adversarial robustness occurs with a non-negligible decline in classification accuracy on clean samples. To tackle this issue, we initially employ the feature activation differences between clean and adversarial examples …

abstract adversarial adversarial training arxiv attention challenge community cs.cr cs.lg overfitting research research community robustness training type