SPOT: Structure Patching and Overlap Tweaking for Effective Pipelining in Privacy-Preserving MLaaS with Tiny Clients. - Xiangrui Xu 004; Qiao Zhang 002; Rui Ning; Chunsheng Xin; Hongyi Wu (ICDCS, 2024)

Comet: A Communication-efficient and Performant Approximation for Private Transformer Inference. - Xiangrui Xu 004; Qiao Zhang 002; Rui Ning; Chunsheng Xin; Hongyi Wu (CoRR, 2024)

AsyncDefender: Dynamic trust adaptation and collaborative defense for Byzantine-robust asynchronous federated learning. - Yulong Bai; Ying Wang; Xiangrui Xu 004; Yuhang Yang; Hina Batool; Zahid Iqbal; Jiuyun Xu (Comput. Networks, 2025)

A two-stage federated learning method for personalization via selective collaboration. - Jiuyun Xu; Liang Zhou; Yingzhi Zhao; Xiaowen Li; Kongshang Zhu; Xiangrui Xu 004; Qiang Duan; Ruru Zhang (Comput. Commun., 2025)

TEG-DI: Dynamic incentive model for Federated Learning based on Tripartite Evolutionary Game. - Jiuyun Xu; Yingzhi Zhao; Xiaowen Li; Liang Zhou; Kongshang Zhu; Xiangrui Xu 004; Qiang Duan; Ruru Zhang (Neurocomputing, 2025)

PrivShap: A Finer-granularity Network Linearization Method for Private Inference. - Xiangrui Xu 004; Zhenzhen Wang; Rui Ning; Chunsheng Xin; Hongyi Wu (Trans. Mach. Learn. Res., 2025)