Selected Publications

Refereed Conference Papers

• BlindGuard: Safeguarding LLM-based Multi-Agent Systems under Unknown Attacks [PDF]
  Rui Miao, Yixin Liu, Yili Wang, Xu Shen, Yue Tan, Yiwei Dai, Shirui Pan, Xin Wang.
  Annual Meeting of the Association for Computational Linguistics (ACL), 2026.

• FedCIGAR: A Personalized Reconstruction Approach for Federated Graph-Level Anomaly Detection [PDF]
  Yunfeng Zhao, Yixin Liu, Qingfeng Chen, Shiyuan Li, Yue Tan, Shirui Pan.
  International Joint Conference on Artificial Intelligence (IJCAI), 2026.

• Multi-Stage Verification-Centric Framework for Mitigating Hallucination in Multi-Modal RAG [PDF]
  Baiyu Chen, Wilson Wongso, Xiaoqian Hu, Yue Tan, Flora Salim.
  Proceedings of the KDD Cup Workshop for Multimodal Retrieval Augmented Generation (CRAG-MM), 2025. (3rd Place, US$1500)

• Bisecle: Binding and Separation in Continual Learning for Video Language Understanding [PDF] [Code]
  Yue Tan, Xiaoqian Hu, Hao Xue, Celso De Melo, Flora D. Salim.
  Thirty-ninth Conference on Neural Information Processing Systems (NeurIPS), 2025.

• A Survey of Generalization of Graph Anomaly Detection: From Transfer Learning to Foundation Models [PDF]
  Junjun Pan, Yu Zheng, Yue Tan, Yixin Liu.
  International Conference on Knowledge Graph (ICKG), 2025.

• Is Heterogeneity Notorious? Taming Heterogeneity to Handle Test-Time Shift in Federated Learning [PDF]
  Yue Tan, Chen Chen, Weiming Zhuang, Xin Dong, Lingjuan Lyu, Guodong Long.
  Thirty-seventh Conference on Neural Information Processing Systems (NeurIPS), 2023.
  A short version has been accepted to SIGKDD Workshop on FL4Data-Mining, 2023.

• Federated Learning on Non-IID Graphs via Structural Knowledge Sharing [PDF] [Code]
  Yue Tan, Yixin Liu, Guodong Long, Jing Jiang, Qinghua Lu, Chengqi Zhang.
  AAAI Conference on Artificial Intelligence (AAAI), 2023. (Oral)

• Federated Learning from Pre-Trained Models: A Contrastive Learning Approach [PDF] [Code]
  Yue Tan, Guodong Long, Jie Ma, Lu Liu, Tianyi Zhou, Jing Jiang.
  Thirty-sixth Conference on Neural Information Processing Systems (NeurIPS), 2022. (Spotlight)
  A short version has been accepted to ICML Workshop on Pre-training, 2022.

• FedProto: Federated Prototype Learning across Heterogeneous Clients [PDF] [Code]
  Yue Tan, Guodong Long, Lu Liu, Tianyi Zhou, Qinghua Lu, Jing Jiang, Chengqi Zhang.
  AAAI Conference on Artificial Intelligence (AAAI), 2022. (15% acceptance rate)

• An In-Vehicle Keyword Spotting System with Multi-Source Fusion for Vehicle Applications [PDF]
  Yue Tan, Kan Zheng, Lei Lei.
  IEEE Wireless Communications and Networking Conference (WCNC), 2019.

Refereed Journal Articles

• Emerging Trends in Federated Learning: From Model Fusion to Federated X Learning [PDF]
  Shaoxiong Ji, Yue Tan, Teemu Saravirta, Zhiqin Yang, Yixin Liu, Lauri Vasankari, Shirui Pan, Guodong Long, Anwar Walid. International Journal of Machine Learning and Cybernetics, 2024.

• LSTM-Based Anomaly Detection for Non-Linear Dynamical System [PDF]
  Yue Tan, Chunjing Hu, Kuan Zhang, Kan Zheng, Ethan A Davis, Jae Sung Park.
  IEEE Access, 2020.

• Dynamic Energy Dispatch Based on Deep Reinforcement Learning in IoT-Driven Smart Isolated Microgrids [PDF]
  Lei Lei, Yue Tan, Glenn Dahlenburg, Wei Xiang, Kan Zheng.
  IEEE Internet of Things Journal, 2020. (IF: 9.94)

• Deep Reinforcement Learning for Autonomous Internet of Things: Model, Applications and Challenges [PDF]
  Lei Lei, Yue Tan, Kan Zheng, Shiwen Liu, Kuan Zhang, Xuemin Shen.
  IEEE Communications Surveys & Tutorials, 2020. (Top-1 Journal in IEEE, IF: 25.25)

Book Chapter

• Federated Learning for Open Banking [LINK]
  Guodong Long, Yue Tan, Jing Jiang, Chengqi Zhang.
  Federated Learning - Privacy and Incentive, Editored by Prof. Qiang Yang, Springer, 2020.

• Federated Learning for Privacy-Preserving Open Innovation Future on Digital Health [LINK]
  Guodong Long, Tao Shen, Yue Tan, Leah Gerrard, Allison Clarke, Jing Jiang.
  Humanity Driven AI, Springer, 2021.

Preprint

• DynHD: Hallucination Detection for Diffusion Large Language Models via Denoising Dynamics Deviation Learning [PDF]
  Yanyu Qian, Yue Tan, Yixin Liu, Wang Yu, Shirui Pan.
  arXiv preprint arXiv:2603.16459, 2026.

• Influence-oriented Personalized Federated Learning [PDF]
  Yue Tan, Guodong Long, Jing Jiang, Chengqi Zhang.
  arXiv preprint arXiv:2410.03315, 2024.