Yuanshun Yao

According to our database, Yuanshun Yao authored at least 34 papers between 2016 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Learning to Watermark LLM-generated Text via Reinforcement Learning.

Xiaojun Xu, Yuanshun Yao, Yang Liu

CoRR, 2024

Improving Reinforcement Learning from Human Feedback Using Contrastive Rewards.

Wei Shen, Xiaoying Zhang, Yuanshun Yao, Rui Zheng, Hongyi Guo, Yang Liu

CoRR, 2024

Fair Classifiers Without Fair Training: An Influence-Guided Data Sampling Approach.

Jinlong Pang, Jialu Wang, Zhaowei Zhu, Yuanshun Yao, Chen Qian, Yang Liu

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

CoRR, 2024

Rethinking Machine Unlearning for Large Language Models.

Sijia Liu, Yuanshun Yao, Jinghan Jia, Stephen Casper, Nathalie Baracaldo, Peter Hase, Xiaojun Xu, Yuguang Yao, Hang Li, Kush R. Varshney, Mohit Bansal, Sanmi Koyejo, Yang Liu

CoRR, 2024

Human-Instruction-Free LLM Self-Alignment with Limited Samples.

Hongyi Guo, Yuanshun Yao, Wei Shen, Jiaheng Wei, Xiaoying Zhang, Zhaoran Wang, Yang Liu

CoRR, 2024

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

Proc. Priv. Enhancing Technol., July, 2023

Large Language Model Unlearning.

Yuanshun Yao, Xiaojun Xu, Yang Liu

CoRR, 2023

Fair Classifiers that Abstain without Harm.

Tongxin Yin, Jean-François Ton, Ruocheng Guo, Yuanshun Yao, Mingyan Liu, Yang Liu

CoRR, 2023

Trustworthy LLMs: a Survey and Guideline for Evaluating Large Language Models' Alignment.

Yang Liu, Yuanshun Yao, Jean-Francois Ton, Xiaoying Zhang, Ruocheng Guo, Hao Cheng, Yegor Klochkov, Muhammad Faaiz Taufiq, Hang Li

CoRR, 2023

Understanding Unfairness via Training Concept Influence.

Yuanshun Yao, Yang Liu

CoRR, 2023

Label Inference Attack against Split Learning under Regression Setting.

Shangyu Xie, Xin Yang, Yuanshun Yao, Tianyi Liu, Taiqing Wang, Jiankai Sun

CoRR, 2023

Weak Proxies are Sufficient and Preferable for Fairness with Missing Sensitive Attributes.

Zhaowei Zhu, Yuanshun Yao, Jiankai Sun, Hang Li, Yang Liu

Proceedings of the International Conference on Machine Learning, 2023

DPAUC: Differentially Private AUC Computation in Federated Learning.

Jiankai Sun, Xin Yang, Yuanshun Yao, Junyuan Xie, Di Wu, Chong Wang

Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022

Learning to Counterfactually Explain Recommendations.

Yuanshun Yao, Chong Wang, Hang Li

CoRR, 2022

Evaluating Fairness Without Sensitive Attributes: A Framework Using Only Auxiliary Models.

Zhaowei Zhu, Yuanshun Yao, Jiankai Sun, Yang Liu, Hang Li

CoRR, 2022

Differentially Private AUC Computation in Vertical Federated Learning.

Jiankai Sun, Xin Yang, Yuanshun Yao, Junyuan Xie, Di Wu, Chong Wang

CoRR, 2022

Differentially Private Label Protection in Split Learning.

Xin Yang, Jiankai Sun, Yuanshun Yao, Junyuan Xie, Chong Wang

CoRR, 2022

Label Leakage and Protection from Forward Embedding in Vertical Federated Learning.

Jiankai Sun, Xin Yang, Yuanshun Yao, Chong Wang

CoRR, 2022

Counterfactually Evaluating Explanations in Recommender Systems.

Yuanshun Yao, Chong Wang, Hang Li

CoRR, 2022

Differentially private multi-party data release for linear regression.

Ruihan Wu, Xin Yang, Yuanshun Yao, Jiankai Sun, Tianyi Liu, Kilian Q. Weinberger, Chong Wang

Proceedings of the Uncertainty in Artificial Intelligence, 2022

2021

Defending against Reconstruction Attack in Vertical Federated Learning.

Jiankai Sun, Yuanshun Yao, Weihao Gao, Junyuan Xie, Chong Wang

CoRR, 2021

Vertical Federated Learning without Revealing Intersection Membership.

Jiankai Sun, Xin Yang, Yuanshun Yao, Aonan Zhang, Weihao Gao, Junyuan Xie, Chong Wang

CoRR, 2021

Backdoor Attacks Against Deep Learning Systems in the Physical World.

Emily Wenger, Josephine Passananti, Arjun Nitin Bhagoji, Yuanshun Yao, Haitao Zheng, Ben Y. Zhao

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2021

2020

Backdoor Attacks on Facial Recognition in the Physical World.

Emily Wenger, Josephine Passananti, Yuanshun Yao, Haitao Zheng, Ben Y. Zhao

CoRR, 2020

2019

Regula Sub-rosa: Latent Backdoor Attacks on Deep Neural Networks.

Yuanshun Yao, Huiying Li, Haitao Zheng, Ben Y. Zhao

CoRR, 2019

Neural Cleanse: Identifying and Mitigating Backdoor Attacks in Neural Networks.

Bolun Wang, Yuanshun Yao, Shawn Shan, Huiying Li, Bimal Viswanath, Haitao Zheng, Ben Y. Zhao

Proceedings of the 2019 IEEE Symposium on Security and Privacy, 2019

Latent Backdoor Attacks on Deep Neural Networks.

Yuanshun Yao, Huiying Li, Haitao Zheng, Ben Y. Zhao

Proceedings of the 2019 ACM SIGSAC Conference on Computer and Communications Security, 2019

2018

With Great Training Comes Great Vulnerability: Practical Attacks against Transfer Learning.

Bolun Wang, Yuanshun Yao, Bimal Viswanath, Haitao Zheng, Ben Y. Zhao

Proceedings of the 27th USENIX Security Symposium, 2018

2017

Identifying Value in Crowdsourced Wireless Signal Measurements.

Zhijing Li, Ana Nika, Xinyi Zhang, Yanzi Zhu, Yuanshun Yao, Ben Y. Zhao, Haitao Zheng

Proceedings of the 26th International Conference on World Wide Web, 2017

Object Recognition and Navigation using a Single Networking Device.

Yanzi Zhu, Yuanshun Yao, Ben Y. Zhao, Haitao Zheng

Proceedings of the 15th Annual International Conference on Mobile Systems, 2017

Complexity vs. performance: empirical analysis of machine learning as a service.

Yuanshun Yao, Zhujun Xiao, Bolun Wang, Bimal Viswanath, Haitao Zheng, Ben Y. Zhao

Proceedings of the 2017 Internet Measurement Conference, 2017

Automated Crowdturfing Attacks and Defenses in Online Review Systems.

Yuanshun Yao, Bimal Viswanath, Jenna Cryan, Haitao Zheng, Ben Y. Zhao

Proceedings of the 2017 ACM SIGSAC Conference on Computer and Communications Security, 2017

2016

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, James H. Faghmous

Proceedings of the 2016 SIAM International Conference on Data Mining, 2016