Network Games with Strategic Machine Learning. - Kun Jin; Tongxin Yin; Charles A. Kamhoua; Mingyan Liu (GameSec, 2021)

An LLM-based Framework for Fingerprinting Internet-connected Devices. - Armin Sarabi; Tongxin Yin; Mingyan Liu (IMC, 2023)

Long-Term Fairness with Unknown Dynamics. - Tongxin Yin; Reilly Raab; Mingyan Liu; Yang Liu 018 (NeurIPS, 2023)

Federated Learning with Reduced Information Leakage and Computation. - Tongxin Yin; Xueru Zhang; Mohammad Mahdi Khalili; Mingyan Liu (CoRR, 2023)

Deterrence, Backup, or Insurance: Game-Theoretic Modeling of Ransomware. - Tongxin Yin; Armin Sarabi; Mingyan Liu (Games, 2023)

Performative Federated Learning: A Solution to Model-Dependent and Heterogeneous Distribution Shifts. - Kun Jin; Tongxin Yin; Zhongzhu Chen; Zeyu Sun; Xueru Zhang; Yang Liu 018; Mingyan Liu (AAAI, 2024)

Leveraging the Physical Layer for Differential Privacy in Over-the-Air Federated Learning. - Jiayu Mao; Tongxin Yin; Aylin Yener; Mingyan Liu (ICC, 2024)

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

Providing Differential Privacy for Federated Learning Over Wireless: A Cross-layer Framework. - Jiayu Mao; Tongxin Yin; Aylin Yener; Mingyan Liu (CoRR, 2024)

Federated Learning with Reduced Information Leakage and Computation. - Tongxin Yin; Xuwei Tan; Xueru Zhang; Mohammad Mahdi Khalili; Mingyan Liu (Trans. Mach. Learn. Res., 2024)

BiasCause: Evaluate Socially Biased Causal Reasoning of Large Language Models. - Tian Xie; Tongxin Yin; Vaishakh Keshava; Xueru Zhang; Siddhartha Reddy Jonnalagadda (CoRR, 2025)