A general framework to increase the robustness of model-based change point detection algorithms to outliers and noise. - Xi C. Chen; Yuanshun Yao; Sichao Shi; Snigdhansu Chatterjee; Vipin Kumar 001; James H. Faghmous (SDM, 2016)

Automated Crowdturfing Attacks and Defenses in Online Review Systems. - Yuanshun Yao; Bimal Viswanath; Jenna Cryan; Haitao Zheng 001; Ben Y. Zhao (CCS, 2017)

Complexity vs. performance: empirical analysis of machine learning as a service. - Yuanshun Yao; Zhujun Xiao; Bolun Wang; Bimal Viswanath; Haitao Zheng 001; Ben Y. Zhao (Internet Measurement Conference, 2017)

Object Recognition and Navigation using a Single Networking Device. - Yanzi Zhu; Yuanshun Yao; Ben Y. Zhao; Haitao Zheng 001 (MobiSys, 2017)

Identifying Value in Crowdsourced Wireless Signal Measurements. - Zhijing Li 001; Ana Nika; Xinyi Zhang 003; Yanzi Zhu; Yuanshun Yao; Ben Y. Zhao; Haitao Zheng 001 (WWW, 2017)

With Great Training Comes Great Vulnerability: Practical Attacks against Transfer Learning. - Bolun Wang; Yuanshun Yao; Bimal Viswanath; Haitao Zheng 001; Ben Y. Zhao (USENIX Security Symposium, 2018)

Latent Backdoor Attacks on Deep Neural Networks. - Yuanshun Yao; Huiying Li 001; Haitao Zheng 001; Ben Y. Zhao (CCS, 2019)

Neural Cleanse: Identifying and Mitigating Backdoor Attacks in Neural Networks. - Bolun Wang; Yuanshun Yao; Shawn Shan; Huiying Li 001; Bimal Viswanath; Haitao Zheng 001; Ben Y. Zhao (IEEE Symposium on Security and Privacy, 2019)

Regula Sub-rosa: Latent Backdoor Attacks on Deep Neural Networks. - Yuanshun Yao; Huiying Li 001; Haitao Zheng 001; Ben Y. Zhao (CoRR, 2019)

Backdoor Attacks on Facial Recognition in the Physical World. - Emily Wenger; Josephine Passananti; Yuanshun Yao; Haitao Zheng 001; Ben Y. Zhao (CoRR, 2020)

Backdoor Attacks Against Deep Learning Systems in the Physical World. - Emily Wenger; Josephine Passananti; Arjun Nitin Bhagoji; Yuanshun Yao; Haitao Zheng 001; Ben Y. Zhao (CVPR, 2021)

Vertical Federated Learning without Revealing Intersection Membership. - Jiankai Sun; Xin Yang 017; Yuanshun Yao; Aonan Zhang; Weihao Gao; Junyuan Xie; Chong Wang 002 (CoRR, 2021)

Defending against Reconstruction Attack in Vertical Federated Learning. - Jiankai Sun; Yuanshun Yao; Weihao Gao; Junyuan Xie; Chong Wang 002 (CoRR, 2021)

Differentially private multi-party data release for linear regression. - Ruihan Wu; Xin Yang 017; Yuanshun Yao; Jiankai Sun; Tianyi Liu; Kilian Q. Weinberger; Chong Wang 002 (UAI, 2022)

Counterfactually Evaluating Explanations in Recommender Systems. - Yuanshun Yao; Chong Wang 002; Hang Li (CoRR, 2022)

Label Leakage and Protection from Forward Embedding in Vertical Federated Learning. - Jiankai Sun; Xin Yang 017; Yuanshun Yao; Chong Wang 002 (CoRR, 2022)

Differentially Private Label Protection in Split Learning. - Xin Yang 017; Jiankai Sun; Yuanshun Yao; Junyuan Xie; Chong Wang 002 (CoRR, 2022)

Differentially Private AUC Computation in Vertical Federated Learning. - Jiankai Sun; Xin Yang 017; Yuanshun Yao; Junyuan Xie; Di Wu; Chong Wang 002 (CoRR, 2022)

Evaluating Fairness Without Sensitive Attributes: A Framework Using Only Auxiliary Models. - Zhaowei Zhu; Yuanshun Yao; Jiankai Sun; Yang Liu 018; Hang Li 001 (CoRR, 2022)

Learning to Counterfactually Explain Recommendations. - Yuanshun Yao; Chong Wang 002; Hang Li (CoRR, 2022)

DPAUC: Differentially Private AUC Computation in Federated Learning. - Jiankai Sun; Xin Yang 017; Yuanshun Yao; Junyuan Xie; Di Wu; Chong Wang 002 (AAAI, 2023)

Weak Proxies are Sufficient and Preferable for Fairness with Missing Sensitive Attributes. - Zhaowei Zhu; Yuanshun Yao; Jiankai Sun; Hang Li 001; Yang Liu 018 (ICML, 2023)

Label Inference Attack against Split Learning under Regression Setting. - Shangyu Xie; Xin Yang 017; Yuanshun Yao; Tianyi Liu; Taiqing Wang; Jiankai Sun (CoRR, 2023)

Understanding Unfairness via Training Concept Influence. - Yuanshun Yao; Yang Liu 018 (CoRR, 2023)

Trustworthy LLMs: a Survey and Guideline for Evaluating Large Language Models' Alignment. - Yang Liu 018; Yuanshun Yao; Jean-Francois Ton; Xiaoying Zhang; Ruocheng Guo; Hao Cheng; Yegor Klochkov; Muhammad Faaiz Taufiq; Hang Li 001 (CoRR, 2023)

Large Language Model Unlearning. - Yuanshun Yao; Xiaojun Xu; Yang Liu 018 (CoRR, 2023)

"My face, my rules": Enabling Personalized Protection Against Unacceptable Face Editing. - Zhujun Xiao; Jenna Cryan; Yuanshun Yao; Yi Hong Gordon Cheo; Yuanchao Shu; Stefan Saroiu; Ben Y. Zhao; Haitao Zheng 001 (Proc. Priv. Enhancing Technol., 2023)

Fair Classifiers that Abstain without Harm. - Tongxin Yin; Jean-Francois Ton; Ruocheng Guo; Yuanshun Yao; Mingyan Liu; Yang Liu 018 (ICLR, 2024)

Fairness without Harm: An Influence-Guided Active Sampling Approach. - Jinlong Pang; Jialu Wang; Zhaowei Zhu; Yuanshun Yao; Chen Qian 001; Yang Liu 018 (NeurIPS, 2024)

Large Language Model Unlearning. - Yuanshun Yao; Xiaojun Xu; Yang Liu (NeurIPS, 2024)

Human-Instruction-Free LLM Self-Alignment with Limited Samples. - Hongyi Guo; Yuanshun Yao; Wei Shen; Jiaheng Wei; Xiaoying Zhang; Zhaoran Wang 001; Yang Liu 018 (CoRR, 2024)

Rethinking Machine Unlearning for Large Language Models. - Sijia Liu 001; Yuanshun Yao; Jinghan Jia; Stephen Casper; Nathalie Baracaldo; Peter Hase; Xiaojun Xu; Yuguang Yao; Hang Li 001; Kush R. Varshney; Mohit Bansal; Sanmi Koyejo; et al. (CoRR, 2024)

Measuring and Reducing LLM Hallucination without Gold-Standard Answers via Expertise-Weighting. - Jiaheng Wei; Yuanshun Yao; Jean-Francois Ton; Hongyi Guo; Andrew Estornell; Yang Liu 018 (CoRR, 2024)

Fair Classifiers Without Fair Training: An Influence-Guided Data Sampling Approach. - Jinlong Pang; Jialu Wang; Zhaowei Zhu; Yuanshun Yao; Chen Qian 001; Yang Liu 018 (CoRR, 2024)

Improving Reinforcement Learning from Human Feedback Using Contrastive Rewards. - Wei Shen; Xiaoying Zhang; Yuanshun Yao; Rui Zheng; Hongyi Guo; Yang Liu 018 (CoRR, 2024)

Learning to Watermark LLM-generated Text via Reinforcement Learning. - Xiaojun Xu; Yuanshun Yao; Yang Liu 018 (CoRR, 2024)

Label Smoothing Improves Machine Unlearning. - Zonglin Di; Zhaowei Zhu; Jinghan Jia; Jiancheng Liu; Zafar Takhirov; Bo Jiang; Yuanshun Yao; Sijia Liu 001; Yang Liu 018 (CoRR, 2024)

Toward Optimal LLM Alignments Using Two-Player Games. - Rui Zheng; Hongyi Guo; Zhihan Liu; Xiaoying Zhang; Yuanshun Yao; Xiaojun Xu; Zhaoran Wang 001; Zhiheng Xi; Tao Gui; Qi Zhang 001; Xuanjing Huang 001; Hang Li 001; et al. (CoRR, 2024)

ACC-Debate: An Actor-Critic Approach to Multi-Agent Debate. - Andrew Estornell; Jean-Francois Ton; Yuanshun Yao; Yang Liu 018 (CoRR, 2024)

Robust Multi-bit Text Watermark with LLM-based Paraphrasers. - Xiaojun Xu; Jinghan Jia; Yuanshun Yao; Yang Liu; Hang Li 001 (CoRR, 2024)

ACC-Collab: An Actor-Critic Approach to Multi-Agent LLM Collaboration. - Andrew Estornell; Jean-Francois Ton; Yuanshun Yao; Yang Liu 018 (ICLR, 2025)

Rethinking machine unlearning for large language models. - Sijia Liu 001; Yuanshun Yao; Jinghan Jia; Stephen Casper; Nathalie Baracaldo; Peter Hase; Yuguang Yao; Chris Yuhao Liu; Xiaojun Xu; Hang Li 001; Kush R. Varshney; Mohit Bansal; et al. (Nat. Mac. Intell., 2025)