Robustness, Privacy, and Generalization of Adversarial Training. - Fengxiang He; Shaopeng Fu; Bohan Wang; Dacheng Tao (CoRR, 2020)

Bayesian Inference Forgetting. - Shaopeng Fu; Fengxiang He; Yue Xu; Dacheng Tao (CoRR, 2021)

Artificial Neural Variability for Deep Learning: On Overfitting, Noise Memorization, and Catastrophic Forgetting. - Zeke Xie; Fengxiang He; Shaopeng Fu; Issei Sato; Dacheng Tao; Masashi Sugiyama (Neural Comput., 2021)

Robust Unlearnable Examples: Protecting Data Privacy Against Adversarial Learning. - Shaopeng Fu; Fengxiang He; Yang Liu 039; Li Shen 008; Dacheng Tao (ICLR, 2022)

Knowledge Removal in Sampling-based Bayesian Inference. - Shaopeng Fu; Fengxiang He; Dacheng Tao (ICLR, 2022)

Robust Unlearnable Examples: Protecting Data Against Adversarial Learning. - Shaopeng Fu; Fengxiang He; Yang Liu 039; Li Shen 008; Dacheng Tao (CoRR, 2022)

Pre-trained Encoder Inference: Revealing Upstream Encoders In Downstream Machine Learning Services. - Shaopeng Fu; Xuexue Sun; Ke Qing; Tianhang Zheng; Di Wang 015 (CoRR, 2024)

Low-carbon building evaluation index system based on hierarchical analysis method. - Ya Zhou; Shaopeng Fu (J. Comput. Methods Sci. Eng., 2024)

"Short-length" Adversarial Training Helps LLMs Defend "Long-length" Jailbreak Attacks: Theoretical and Empirical Evidence. - Shaopeng Fu; Liang Ding; Di Wang (CoRR, 2025)

C2 ATTACK: Towards Representation Backdoor on CLIP via Concept Confusion. - Lijie Hu; Junchi Liao; Weimin Lyu; Shaopeng Fu; Tianhao Huang; Shu Yang 010; Guimin Hu; Di Wang 015 (CoRR, 2025)

Theoretical Analysis of Robust Overfitting for Wide DNNs: An NTK Approach. - Shaopeng Fu; Di Wang 015 (IEEE Trans. Inf. Theory, 2025)