187 citations · 293 across the 33 of their papers we have counts for
Showing 2023 · cs.LGShow all
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cs.LG2023★ 3 cited
Mitigating Accuracy-Robustness Trade-off via Balanced Multi-Teacher Adversarial Distillation
Shiji Zhao, Xizhe Wang, Xingxing Wei
Adversarial Training is a practical approach for improving the robustness of deep neural networks against adversarial attacks. Although bringing reliable robustness, the performanc…
cs.LG2023★ 4 cited
Improving Fast Adversarial Training with Prior-Guided Knowledge
Xiaojun Jia, Yong Zhang, Xingxing Wei +4
Fast adversarial training (FAT) is an efficient method to improve robustness. However, the original FAT suffers from catastrophic overfitting, which dramatically and suddenly reduc…