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cs.CV2026
Adaptive Causal Alignment for High-Confidence Adversarial Training
Zhiming Luo, Kejia Zhang, Yingxin Lai +3
Inverse adversarial training leverages high-confidence predictions to stabilize robust learning, yet we uncover a critical paradox: high confidence often stems from overfitting to…
cs.CV2025
MANI-Pure: Magnitude-Adaptive Noise Injection for Adversarial Purification
Xiaoyi Huang, Junwei Wu, Kejia Zhang +2
Adversarial purification with diffusion models has emerged as a promising defense strategy, but existing methods typically rely on uniform noise injection, which indiscriminately p…
cs.CV2024★ 1 cited
Harmonizing Feature Maps: A Graph Convolutional Approach for Enhancing Adversarial Robustness
Kejia Zhang, Juanjuan Weng, Junwei Wu +3
The vulnerability of Deep Neural Networks to adversarial perturbations presents significant security concerns, as the imperceptible perturbations can contaminate the feature space…