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

B. Wang, Y. Yao, S. Shan, H. Li, B. Viswanath, H. Zheng, и B. Zhao. IEEE Symposium on Security and Privacy, стр. 707-723. IEEE, (2019)

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Yao Yao

Hongmei Yao

Ning Yao

Haimin Yao

Yefeng Yao

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Complexity vs. performance: empirical analysis of machine learning as a service.Y. Yao, Z. Xiao, B. Wang, B. Viswanath, H. Zheng, и B. Zhao. Internet Measurement Conference, стр. 384-397. ACM, (2017)Learning to Watermark LLM-generated Text via Reinforcement Learning.X. Xu, Y. Yao, и Y. Liu. CoRR, (2024)Fair Classifiers that Abstain without Harm.T. Yin, J. Ton, R. Guo, Y. Yao, M. Liu, и Y. Liu. CoRR, (2023)Trustworthy LLMs: a Survey and Guideline for Evaluating Large Language Models' Alignment.Y. Liu, Y. Yao, J. Ton, X. Zhang, R. Guo, H. Cheng, Y. Klochkov, M. Taufiq, и H. Li. CoRR, (2023)Improving Reinforcement Learning from Human Feedback Using Contrastive Rewards.W. Shen, X. Zhang, Y. Yao, R. Zheng, H. Guo, и Y. Liu. CoRR, (2024)DPAUC: Differentially Private AUC Computation in Federated Learning.J. Sun, X. Yang, Y. Yao, J. Xie, D. Wu, и C. Wang. AAAI, стр. 15170-15178. AAAI Press, (2023)Toward Optimal LLM Alignments Using Two-Player Games.R. Zheng, H. Guo, Z. Liu, X. Zhang, Y. Yao, X. Xu, Z. Wang, Z. Xi, T. Gui, Q. Zhang и 3 other автор(ы). CoRR, (2024)Evaluating Fairness Without Sensitive Attributes: A Framework Using Only Auxiliary Models.Z. Zhu, Y. Yao, J. Sun, Y. Liu, и H. Li. CoRR, (2022)Measuring and Reducing LLM Hallucination without Gold-Standard Answers via Expertise-Weighting.J. Wei, Y. Yao, J. Ton, H. Guo, A. Estornell, и Y. Liu. CoRR, (2024)Fair Classifiers that Abstain without Harm.T. Yin, J. Ton, R. Guo, Y. Yao, M. Liu, и Y. Liu. ICLR, OpenReview.net, (2024)

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