Sample-wise Targeted Adversarial Attacks on Test-time Adaptation
This work proposes a meta-learning-based attack with a novel priority-aware gradient alignment strategy that explicitly prioritizes attack success, and formulates the gradient update as an ellipsoidal trust-region problem, mitigating gradient conflict between the attack and stealth objectives, while providing theoretic...