Live Gradient Compensation for Evading Stragglers in Distributed Learning. - Jian Xu 016; Shao-Lun Huang; Linqi Song; Tian Lan 001 (INFOCOM, 2021)

SignGuard: Byzantine-robust Federated Learning through Collaborative Malicious Gradient Filtering. - Jian Xu 016; Shao-Lun Huang; Linqi Song; Tian Lan 001 (CoRR, 2021)

Federated Capsule Graph Neural Network with Personalization. - Meilin Yang; Jian Xu 016; Wenbo Ding 001; Yang Liu 165 (UbiComp/ISWC Adjunct, 2022)

Byzantine-Resilient Decentralized Collaborative Learning. - Jian Xu 016; Shao-Lun Huang (ICASSP, 2022)

Communication-Efficient and Byzantine-Robust Distributed Stochastic Learning with Arbitrary Number of Corrupted Workers. - Jian Xu 016; Xinyi Tong 002; Shao-Lun Huang (ICC, 2022)

Byzantine-robust Federated Learning through Collaborative Malicious Gradient Filtering. - Jian Xu 016; Shao-Lun Huang; Linqi Song; Tian Lan 001 (ICDCS, 2022)

FedPer++: Toward Improved Personalized Federated Learning on Heterogeneous and Imbalanced Data. - Jian Xu 016; Yi Yan; Shao-Lun Huang (IJCNN, 2022)

An Information-theoretic Method for Collaborative Distributed Learning with Limited Communication. - Xinyi Tong 002; Jian Xu 016; Shao-Lun Huang (ITW, 2022)

A Joint Training-Calibration Framework for Test-Time Personalization with Label Shift in Federated Learning. - Jian Xu 016; Shao-Lun Huang (CIKM, 2023)

Personalized Federated Learning with Feature Alignment and Classifier Collaboration. - Jian Xu 016; Xinyi Tong 002; Shao-Lun Huang (ICLR, 2023)

Mitigating Model Poisoning Attacks on Distributed Learning with Heterogeneous Data. - Jian Xu 016; Guangfeng Yan; Ziyan Zheng; Shao-Lun Huang (ICMLA, 2023)

Stabilizing and Improving Federated Learning with Non-IID Data and Client Dropout. - Jian Xu 016; Meiling Yang; Wenbo Ding 001; Shao-Lun Huang (CoRR, 2023)

NAC: Mitigating Noisy Correspondence in Cross-Modal Matching Via Neighbor Auxiliary Corrector. - Yuqing Li; Haoming Huang; Jian Xu 016; Shao-Lun Huang (ICASSP, 2024)

PSformer: Parameter-efficient Transformer with Segment Attention for Time Series Forecasting. - Yanlong Wang; Jian Xu 016; Fei Ma; Shao-Lun Huang; Danny Dongning Sun; Xiao-Ping Zhang (CoRR, 2024)

On the Fundamental Limit of Distributed Learning With Interchangable Constrained Statistics. - Xinyi Tong 002; Jian Xu 016; Shao-Lun Huang (IEEE J. Sel. Areas Inf. Theory, 2024)

FedHAP: Federated Hashing With Global Prototypes for Cross-Silo Retrieval. - Meilin Yang; Jian Xu 016; Wenbo Ding 001; Yang Liu 165 (IEEE Trans. Parallel Distributed Syst., 2024)

pFedGPA: Diffusion-based Generative Parameter Aggregation for Personalized Federated Learning. - Jiahao Lai; Jiaqi Li; Jian Xu 016; Yanru Wu; Boshi Tang; Siqi Chen; Yongfeng Huang; Wenbo Ding 001; Yang Li (AAAI, 2025)

RALLRec: Improving Retrieval Augmented Large Language Model Recommendation with Representation Learning. - Jian Xu 016; Sichun Luo; Xiangyu Chen; Haoming Huang; Hanxu Hou; Linqi Song (WWW (Companion Volume), 2025)

Cooperative Multi-Model Training for Personalized Federated Learning Over Heterogeneous Devices. - Jian Xu 016; Shuo Wan; Yinchuan Li; Sichun Luo; Zhilin Chen; Yunfeng Shao 001; Zhitang Chen; Shao-Lun Huang; Linqi Song (IEEE J. Sel. Top. Signal Process., 2025)

Stabilizing and improving federated learning with highly non-iid data and client dropout. - Jian Xu 016; Meilin Yang; Wenbo Ding 001; Shao-Lun Huang (Appl. Intell., 2025)

RALLRec+: Retrieval Augmented Large Language Model Recommendation with Reasoning. - Sichun Luo; Jian Xu 016; Xiaojie Zhang; Linrong Wang; Sicong Liu; Hanxu Hou; Linqi Song (CoRR, 2025)

Reasoning Meets Personalization: Unleashing the Potential of Large Reasoning Model for Personalized Generation. - Sichun Luo; Guanzhi Deng; Jian Xu 016; Xiaojie Zhang; Hanxu Hou; Linqi Song (CoRR, 2025)