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20242026
most citedNew Paradigm of Adversarial Training: Releasing Accuracy-Robustness Trade-Off via Dummy Class

1 citations · 1 across the 5 of their papers we have counts for

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cs.CV2026

Steering the Flow: Inverting Face Recognition Models via Gradient-Guided Flow Matching

Ye Lu, Shen Wang, Zhaoyang Zhang +4

Model Inversion Attacks (MIAs) aim to reconstruct representative training samples of target identities from face recognition models, exposing critical security vulnerabilities. Exi…

cs.CV2026

Robust Alignment: Harmonizing Clean Accuracy and Adversarial Robustness in Adversarial Training

Yanyun Wang, Qingqing Ye, Li Liu +2

Adversarial Training (AT) is one of the most effective methods for developing robust deep neural networks (DNNs). However, AT faces a trade-off problem between clean accuracy and a…