Dynamic-Weighted Contrastive Adversarial Training
Adversarial training (AT) is a mainstream paradigm for improving the robustness of deep models. However, natural and adversarial examples often exhibit distributional discrepancies in feature space, and fixed-weight contrastive constraints can conflict with classification learning when applied throughout training. To a...