2 papers
cs.LG2026
When Muon Optimizer Meets Adversarial Training: A Theoretical and Empirical Study
Jun Yan, Weiquan Huang, Jiankai Zuo +4
Adversarial training (AT) remains one of the most reliable empirical defenses against adversarial attacks. Its robustness critically depends on how the underlying min-max objective…
cs.CV2024
Segment-Anything Models Achieve Zero-shot Robustness in Autonomous Driving
Jun Yan, Pengyu Wang, Danni Wang +3
Semantic segmentation is a significant perception task in autonomous driving. It suffers from the risks of adversarial examples. In the past few years, deep learning has gradually…