LAFEAT: Piercing Through Adversarial Defenses With Latent Features. - Yunrui Yu; Xitong Gao; Cheng-Zhong Xu 001 (CVPR, 2021)

Adversarial Attacks on ML Defense Models Competition. - Yinpeng Dong; Qi-An Fu; Xiao Yang; Wenzhao Xiang 001; Tianyu Pang; Hang Su 006; Jun Zhu 001; Jiayu Tang; Yuefeng Chen; Xiaofeng Mao; Yuan He 011; Hui Xue 001; et al. (CoRR, 2021)

MORA: Improving Ensemble Robustness Evaluation with Model Reweighing Attack. - Yunrui Yu; Xitong Gao; Cheng-Zhong Xu 001 (NeurIPS, 2022)

Efficient Loss Function by Minimizing the Detrimental Effect of Floating-Point Errors on Gradient-Based Attacks. - Yunrui Yu; Cheng-Zhong Xu 001 (CVPR, 2023)

LAFIT: Efficient and Reliable Evaluation of Adversarial Defenses With Latent Features. - Yunrui Yu; Xitong Gao; Cheng-Zhong Xu 001 (IEEE Trans. Pattern Anal. Mach. Intell., 2024)

Theoretical Analysis of Relative Errors in Gradient Computations for Adversarial Attacks with CE Loss. - Yunrui Yu; Hang Su; Cheng-zhong Xu 001; Zhizhong Su; Jun Zhu (CoRR, 2025)

RCR-AF: Enhancing Model Generalization via Rademacher Complexity Reduction Activation Function. - Yunrui Yu; Kafeng Wang; Hang Su; Jun Zhu (CoRR, 2025)