Automatic Ensemble Learning for Online Influence Maximization. - Xiaojin Zhang 002 (CoRR, 2019)

Near-Optimal Algorithm for Distribution-Free Junta Testing. - Xiaojin Zhang 002 (CoRR, 2019)

Contextual Combinatorial Conservative Bandits. - Xiaojin Zhang 002; Shuai Li 010; Weiwen Liu (CoRR, 2019)

Adaptive Double-Exploration Tradeoff for Outlier Detection. - Xiaojin Zhang 002; Honglei Zhuang; Shengyu Zhang; Yuan Zhou 007 (AAAI, 2020)

Achieving Near Instance-Optimality and Minimax-Optimality in Stochastic and Adversarial Linear Bandits Simultaneously. - Chung-Wei Lee; Haipeng Luo; Chen-Yu Wei; Mengxiao Zhang; Xiaojin Zhang 002 (ICML, 2021)

Variance-dependent best arm identification. - Pinyan Lu; Chao Tao; Xiaojin Zhang 002 (UAI, 2021)

A Framework for Evaluating Privacy-Utility Trade-off in Vertical Federated Learning. - Yan Kang 001; Jiahuan Luo; Yuanqin He; Xiaojin Zhang 002; Lixin Fan; Qiang Yang 001 (CoRR, 2022)

Toward the Tradeoffs Between Privacy, Fairness and Utility in Federated Learning. - Kangkang Sun; Xiaojin Zhang 002; Xi Lin 003; Gaolei Li; Jing Wang; Jianhua Li 001 (EISA, 2023)

Probably Approximately Correct Federated Learning. - Xiaojin Zhang 002; Anbu Huang; Lixin Fan; Kai Chen 005; Qiang Yang 001 (CoRR, 2023)

A Game-theoretic Framework for Federated Learning. - Xiaojin Zhang 002; Lixin Fan; Siwei Wang; Wenjie Li 008; Kai Chen 005; Qiang Yang 001 (CoRR, 2023)

Towards Achieving Near-optimal Utility for Privacy-Preserving Federated Learning via Data Generation and Parameter Distortion. - Xiaojin Zhang 002; Kai Chen 005; Qiang Yang 001 (CoRR, 2023)

Theoretically Principled Federated Learning for Balancing Privacy and Utility. - Xiaojin Zhang 002; Wenjie Li 008; Kai Chen 005; Shutao Xia; Qiang Yang 001 (CoRR, 2023)

Privacy in Large Language Models: Attacks, Defenses and Future Directions. - Haoran Li 003; Yulin Chen; Jinglong Luo; Yan Kang 001; Xiaojin Zhang 002; Qi Hu; Chunkit Chan; Yangqiu Song (CoRR, 2023)

K-ESConv: Knowledge Injection for Emotional Support Dialogue Systems via Prompt Learning. - Wei Chen 088; Gang Zhao; Xiaojin Zhang 002; Xiang Bai; Xuanjing Huang 001; Zhongyu Wei (CoRR, 2023)

No Free Lunch Theorem for Security and Utility in Federated Learning. - Xiaojin Zhang 002; Hanlin Gu; Lixin Fan; Kai Chen 005; Qiang Yang 001 (ACM Trans. Intell. Syst. Technol., 2023)

Trading Off Privacy, Utility, and Efficiency in Federated Learning. - Xiaojin Zhang 002; Yan Kang 001; Kai Chen 005; Lixin Fan; Qiang Yang 001 (ACM Trans. Intell. Syst. Technol., 2023)

Model Trip: Enhancing Privacy and Fairness in Model Fusion Across Multi-Federations for Trustworthy Global Healthcare. - Qian Chen; Yiqiang Chen 001; Bingjie Yan; Xinlong Jiang; Xiaojin Zhang 002; Yan Kang 001; Teng Zhang; Wuliang Huang; Chenlong Gao; Lixin Fan; Qiang Yang 001 (ICDE, 2024)

Secure Dataset Condensation for Privacy-Preserving and Efficient Vertical Federated Learning. - Dashan Gao 002; Canhui Wu; Xiaojin Zhang 002; Xin Yao; Qiang Yang 001 (ECML/PKDD (1), 2024)

CauESC: A Causal Aware Model for Emotional Support Conversation. - Wei Chen 088; Hengxu Lin; Qun Zhang; Xiaojin Zhang 002; Xiang Bai; Xuanjing Huang 001; Zhongyu Wei (CoRR, 2024)

Reinforcement Learning as a Catalyst for Robust and Fair Federated Learning: Deciphering the Dynamics of Client Contributions. - Jialuo He; Wei Chen 088; Xiaojin Zhang 002 (CoRR, 2024)

Deciphering the Interplay between Local Differential Privacy, Average Bayesian Privacy, and Maximum Bayesian Privacy. - Xiaojin Zhang 002; Yulin Fei; Wei Chen 088 (CoRR, 2024)

Beyond ESM2: Graph-Enhanced Protein Sequence Modeling with Efficient Clustering. - Shujian Jiao; Bingxuan Li; Lei Wang; Xiaojin Zhang 002; Wei Chen 088; Jiajie Peng; Zhongyu Wei (CoRR, 2024)

No Free Lunch Theorem for Privacy-Preserving LLM Inference. - Xiaojin Zhang 002; Yulin Fei; Yan Kang 001; Wei Chen 088; Lixin Fan; Hai Jin 001; Qiang Yang 001 (CoRR, 2024)

VulDetectBench: Evaluating the Deep Capability of Vulnerability Detection with Large Language Models. - Yu Liu; Lang Gao; Mingxin Yang; Yu Xie; Ping Chen; Xiaojin Zhang 002; Wei Chen 088 (CoRR, 2024)

A Unified Learn-to-Distort-Data Framework for Privacy-Utility Trade-off in Trustworthy Federated Learning. - Xiaojin Zhang 002; Mingcong Xu; Wei Chen 088 (CoRR, 2024)

Theoretical Analysis of Privacy Leakage in Trustworthy Federated Learning: A Perspective from Linear Algebra and Optimization Theory. - Xiaojin Zhang 002; Wei Chen 088 (CoRR, 2024)

MC-CoT: A Modular Collaborative CoT Framework for Zero-shot Medical-VQA with LLM and MLLM Integration. - Lai Wei; Wenkai Wang; Xiaoyu Shen; Yu Xie; Zhihao Fan; Xiaojin Zhang 002; Zhongyu Wei; Wei Chen 088 (CoRR, 2024)

RSL-SQL: Robust Schema Linking in Text-to-SQL Generation. - Zhenbiao Cao; Yuanlei Zheng; Zhihao Fan; Xiaojin Zhang 002; Wei Chen 088; Xiang Bai (CoRR, 2024)

Fed-AugMix: Balancing Privacy and Utility via Data Augmentation. - Haoyang Li; Wei Chen 088; Xiaojin Zhang 002 (CoRR, 2024)

Corrigendum to "Improved Algorithm for Permutation Testing" [Theoretical Computer Science 986 (2024) 114316]. - Xiaojin Zhang 002 (Theor. Comput. Sci., 2024)

Improved algorithm for permutation testing. - Xiaojin Zhang 002 (Theor. Comput. Sci., 2024)

A Game-theoretic Framework for Privacy-preserving Federated Learning. - Xiaojin Zhang 002; Lixin Fan; Siwei Wang; Wenjie Li 008; Kai Chen 005; Qiang Yang 001 (ACM Trans. Intell. Syst. Technol., 2024)

A Meta-Learning Framework for Tuning Parameters of Protection Mechanisms in Trustworthy Federated Learning. - Xiaojin Zhang 002; Yan Kang 001; Lixin Fan; Kai Chen 005; Qiang Yang 001 (ACM Trans. Intell. Syst. Technol., 2024)

FedAA: A Reinforcement Learning Perspective on Adaptive Aggregation for Fair and Robust Federated Learning. - Jialuo He; Wei Chen 088; Xiaojin Zhang 002 (AAAI, 2025)

Do Current Video LLMs Have Strong OCR Abilities? A Preliminary Study. - Yulin Fei; Yuhui Gao; Xingyuan Xian; Xiaojin Zhang 002; Tao Wu; Wei Chen 088 (COLING, 2025)

No free lunch theorem for privacy-preserving LLM inference. - Xiaojin Zhang 002; Yahao Pang; Yan Kang 001; Wei Chen 088; Lixin Fan; Hai Jin 001; Qiang Yang 001 (Artif. Intell., 2025)

InsQABench: Benchmarking Chinese Insurance Domain Question Answering with Large Language Models. - Jing Ding; Kai Feng; Binbin Lin; Jiarui Cai; Qiushi Wang; Yu Xie; Xiaojin Zhang 002; Zhongyu Wei; Wei Chen 088 (CoRR, 2025)

FedEAT: A Robustness Optimization Framework for Federated LLMs. - Yahao Pang; Xingyuan Wu; Xiaojin Zhang 002; Wei Chen 088; Hai Jin 001 (CoRR, 2025)

FedEM: A Privacy-Preserving Framework for Concurrent Utility Preservation in Federated Learning. - Mingcong Xu; Xiaojin Zhang 002; Wei Chen 088; Hai Jin 001 (CoRR, 2025)

FedSDAF: Leveraging Source Domain Awareness for Enhanced Federated Domain Generalization. - Hongze Li; Zesheng Zhou; Zhenbiao Cao; Xinhui Li; Wei Chen 088; Xiaojin Zhang 002 (CoRR, 2025)

Ten Challenging Problems in Federated Foundation Models. - Tao Fan 002; Hanlin Gu; Xuemei Cao 001; Chee Seng Chan; Qian Chen; Yiqiang Chen 001; Yihui Feng; Yang Gu 001; Jiaxiang Geng; Bing Luo; Shuoling Liu; WinKent Ong; et al. (IEEE Trans. Knowl. Data Eng., 2025)

Camouflaged Variational Graph AutoEncoder Against Attribute Inference Attacks for Cross-Domain Recommendation. - Yudi Xiong; Yongxin Guo; Weike Pan; Qiang Yang 001; Zhong Ming 001; Xiaojin Zhang 002; Han Yu 001; Tao Lin; Xiaoying Tang 002 (IEEE Trans. Knowl. Data Eng., 2025)

Deciphering the Interplay between Attack and Protection Complexity in Privacy-Preserving Federated Learning. - Xiaojin Zhang 002; Mingcong Xu; Yiming Li; Wei Chen 088; Qiang Yang 001 (CoRR, 2025)

Grounding Foundation Models through Federated Transfer Learning: A General Framework. - Yan Kang 001; Tao Fan 002; Hanlin Gu; Xiaojin Zhang 002; Lixin Fan; Qiang Yang 001 (ACM Trans. Intell. Syst. Technol., 2025)