| 2026 | AAAI | Multi-Objective Bilevel Learning. | Zhiyao Zhang, Zhuqing Liu, Xin Zhang, Wen-Yen Chen, Jiyan Yang, Jia Liu |
| 2026 | AsiaCCS | SecureAFL: Secure Asynchronous Federated Learning. | Anjun Gao, Feng Wang, Zhenglin Wan, Yueyang Quan, Zhuqing Liu, Minghong Fang |
| 2026 | WWW | SecureSplit: Mitigating Backdoor Attacks in Split Learning. | Zhihao Dou, Dongfei Cui, Weida Wang, Anjun Gao, Yueyang Quan, Mengyao Ma, Viet Vo, Guangdong Bai, Zhuqing Liu, Minghong Fang |
| 2026 | SP | Who Taught the Lie? Responsibility Attribution for Poisoned Knowledge in Retrieval-Augmented Generation. | Baolei Zhang, Haoran Xin, Yuxi Chen, Zhuqing Liu, Biao Yi, Tong Li, Lihai Nie, Zheli Liu, Minghong Fang |
| 2026 | SACMAT | Practical Poisoning Attacks against Retrieval-Augmented Generation. | Baolei Zhang, Yuxi Chen, Zhuqing Liu, Lihai Nie, Tong Li, Zheli Liu, Minghong Fang |
| 2026 | WiOpt | When the Server Steps In: Calibrated Updates for Fair Federated Learning. | Tianrun Yu, Kaixiang Zhao, Cheng Zhang, Anjun Gao, Yueyang Quan, Zhuqing Liu, Minghong Fang |
| 2025 | AsiaCCS | Toward Malicious Clients Detection in Federated Learning. | Zhihao Dou, Jiaqi Wang, Wei Sun, Zhuqing Liu, Minghong Fang |
| 2025 | ICLR | DUET: Decentralized Bilevel Optimization without Lower-Level Strong Convexity. | Zhen Qin, Zhuqing Liu, Songtao Lu, Yingbin Liang, Jia Liu |
| 2025 | MOBIHOC | Enhancing Privacy in Decentralized Min-Max Optimization: A Differentially Private Approach. | Yueyang Quan, Chang Wang, Shengjie Zhai, Minghong Fang, Zhuqing Liu |
| 2025 | NDSS | Do We Really Need to Design New Byzantine-robust Aggregation Rules? | Minghong Fang, Seyedsina Nabavirazavi, Zhuqing Liu, Wei Sun, Sundaraja Sitharama Iyengar, Haibo Yang |
| 2025 | WWW | Byzantine-Robust Federated Learning over Ring-All-Reduce Distributed Computing. | Minghong Fang, Zhuqing Liu, Xuecen Zhao, Jia Liu |
| 2025 | WWW | Poisoning Attacks and Defenses to Federated Unlearning. | Wenbin Wang, Qiwen Ma, Zifan Zhang, Yuchen Liu, Zhuqing Liu, Minghong Fang |
| 2025 | WWW | Traceback of Poisoning Attacks to Retrieval-Augmented Generation. | Baolei Zhang, Haoran Xin, Minghong Fang, Zhuqing Liu, Biao Yi, Tong Li, Zheli Liu |
| 2025 | TrustCom | Fairness-Constrained Optimization Attack in Federated Learning. | Harsh Kasyap, Minghong Fang, Zhuqing Liu, Carsten Maple, Somanath Tripathy |
| 2025 | UAI | STIMULUS: Achieving Fast Convergence and Low Sample Complexity in Stochastic Multi-Objective Learning. | Zhuqing Liu, Chaosheng Dong, Michinari Momma, Simone Shao, Shaoyuan Xu, Yan Gao, Haibo Yang, Jia Liu |
| 2024 | ICLR | PILOT: An $\mathcal{O}(1/K)$-Convergent Approach for Policy Evaluation with Nonlinear Function Approximation. | Zhuqing Liu, Xin Zhang, Jia Liu, Zhengyuan Zhu, Songtao Lu |
| 2023 | ICML | Prometheus: Taming Sample and Communication Complexities in Constrained Decentralized Stochastic Bilevel Learning. | Zhuqing Liu, Xin Zhang, Prashant Khanduri, Songtao Lu, Jia Liu |
| 2023 | INFOCOM | DIAMOND: Taming Sample and Communication Complexities in Decentralized Bilevel Optimization. | Peiwen Qiu, Yining Li, Zhuqing Liu, Prashant Khanduri, Jia Liu, Ness B. Shroff, Elizabeth Serena Bentley, Kurt A. Turck |
| 2023 | MOBIHOC | PRECISION: Decentralized Constrained Min-Max Learning with Low Communication and Sample Complexities. | Zhuqing Liu, Xin Zhang, Songtao Lu, Jia Liu |
| 2022 | MOBIHOC | INTERACT: achieving low sample and communication complexities in decentralized bilevel learning over networks. | Zhuqing Liu, Xin Zhang, Prashant Khanduri, Songtao Lu, Jia Liu |
| 2022 | MOBIHOC | SYNTHESIS: a semi-asynchronous path-integrated stochastic gradient method for distributed learning in computing clusters. | Zhuqing Liu, Xin Zhang, Jia Liu |
| 2022 | MOBIHOC | NET-FLEET: achieving linear convergence speedup for fully decentralized federated learning with heterogeneous data. | Xin Zhang, Minghong Fang, Zhuqing Liu, Haibo Yang, Jia Liu, Zhengyuan Zhu |