Publications

Conference

• Rethinking Feature Alignment in Generalist Graph Anomaly Detection: A Relational Fingerprint-based Approach
  Yujing Liu, Yixin Liu, Yu Zheng, Alan Wee-Chung Liew, Xiaofeng Cao, Shirui Pan.
  Proceedings of the International Conference on Machine Learning (ICML), 2026.

• Towards One-for-All Anomaly Detection for Tabular Data
  Shiyuan Li, Yixin Liu, Yu Zheng, Xiaofeng Cao, Shirui Pan, Heng Tao Shen.
  Proceedings of the International Conference on Machine Learning (ICML), 2026.

• OFA-MAS: One-for-All Multi-Agent System Topology Design based on Mixture-of-Experts Graph Generative Models [PDF]
  Shiyuan Li*, Yixin Liu*, Yu Zheng, Mei Li, Quoc Viet Hung Nguyen, Shirui Pan.
  ACM Web Conference (WWW), 2026.

• BlindGuard: Safeguarding LLM-based Multi-Agent Systems under Unknown Attacks
  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.

• Explainable and Fine-Grained Safeguarding of LLM Multi-Agent Systems via Bi-Level Graph Anomaly Detection
  Junjun Pan, Yixin Liu†, Rui Miao, Kaize Ding, Yu Zheng, Quoc Viet Hung Nguyen, Alan Wee-Chung Liew, Shirui Pan.
  Annual Meeting of the Association for Computational Linguistics (ACL), 2026.

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

• CAMERA: Adapting to Semantic Camouflage in Unsupervised Text-Attributed Graph Fraud Detection
  Junjun Pan, Yixin Liu†, Yu Zheng†, Lianhua Chi, Alan Wee-Chung Liew, Shirui Pan.
  International Joint Conference on Artificial Intelligence (IJCAI), 2026.

• Assemble Your Crew: Automatic Multi-Agent Communication Topology Design via Autoregressive Graph Generation [PDF] [Code]
  Shiyuan Li, Yixin Liu, Qingsong Wen, Chengqi Zhang, Shirui Pan.
  AAAI Conference on Artificial Intelligence (AAAI), 2026.

• Correcting False Alarms from Unseen: Adapting Graph Anomaly Detectors at Test Time [PDF] [Code]
  Junjun Pan, Yixin Liu, Chuan Zhou, Fei Xiong, Alan Wee-Chung Liew, Shirui Pan.
  AAAI Conference on Artificial Intelligence (AAAI), 2026.

• Beyond a Single Perspective: Text Anomaly Detection with Multi-View Language Representations
  Yixin Liu, Kehan Yan, Shiyuan Li, Qingfeng Chen, Shirui Pan.
  European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML-PKDD), 2026.

• IAMRec: Intent-Adaptive Multimodal Recommendation with Collaborative–Modality Disentanglement
  Jiayi Chen, Xin Zheng, Yixin Liu, Yi Li, Yanqing Guo, Shirui Pan.
  Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD), 2026.

• 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.

• FreeGAD: A Training-Free yet Effective Approach for Graph Anomaly Detection [PDF] [Code]
  Yunfeng Zhao, Yixin Liu*, Shiyuan Li, Qingfeng Chen, Yu Zheng, Shirui Pan.
  ACM International Conference on Information and Knowledge Management (CIKM), 2025.

• Understanding the Information Propagation Effects of Communication Topologies in LLM-based Multi-Agent Systems [PDF] [Code]
  Xu Shen*, Yixin Liu*, Yiwei Dai, Yili Wang, Rui Miao, Yue Tan, Shirui Pan, Xin Wang.
  Conference on Empirical Methods in Natural Language Processing (EMNLP), 2025.

• SpecG: A Spectral-based Framework for Effective Graph Pre-training and Knowledge Transfer [PDF]
  Zizhe Jin, Yizhen Zheng, Linhao Luo, Yixin Liu, Xin Zheng, Xuefei Yin, Vincent Lee, Shirui Pan.
  Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD), 2025.

• Unifying Unsupervised Graph-level Anomaly Detection and Out-of-distribution Detection: A Benchmark [PDF] [Code]
  Yili Wang, Yixin Liu*, Xu Shen, Chenyu Li, Kaize Ding, Rui Miao, Ying Wang, Shirui Pan, Xin Wang.
  International Conference on Learning Representations (ICLR), 2025.

• A Label-free Heterophily-guided Approach for Unsupervised Graph Fraud Detection [PDF] [Code]
  Junjun Pan, Yixin Liu, Xin Zheng, Yizhen Zheng, Alan Wee-Chung Liew, Fuyi Li, Shirui Pan.
  AAAI Conference on Artificial Intelligence (AAAI), 2025.

• ARC: A Generalist Graph Anomaly Detector with In-Context Learning [PDF] [Code]
  Yixin Liu, Shiyuan Li, Yu Zheng, Qingfeng Chen, Chengqi Zhang, Shirui Pan.
  Advances in Neural Information Processing Systems (NeurIPS), 2024.

• Self-Supervision Improves Diffusion Models for Tabular Data Imputation [PDF] [Code]
  Yixin Liu, Thalaiyasingam Ajanthan, Hisham Husain, Vu Nguyen.
  ACM International Conference on Information and Knowledge Management (CIKM), 2024.

• Noise-Resilient Unsupervised Graph Representation Learning via Multi-Hop Feature Quality Estimation [PDF] [Code]
  Shiyuan Li*, Yixin Liu*, Qingfeng Chen, Geoffrey Webb, Shirui Pan.
  ACM International Conference on Information and Knowledge Management (CIKM), 2024.

• Divide and Denoise: Empowering Simple Models for Robust Semi-Supervised Node Classification [PDF] [Code]
  Kaize Ding, Xiaoxiao Ma, Yixin Liu, Shirui Pan.
  ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2024.

• GOODAT: Towards Test-time Graph Out-of-Distribution Detection [PDF] [Code]
  Luzhi Wang, Di Jin, He Zhang, Yixin Liu, Dongxiao He, Wenjie Wang, Shirui Pan, Tat-Seng Chua.
  AAAI Conference on Artificial Intelligence (AAAI), 2024.

• Towards Self-Interpretable Graph-Level Anomaly Detection [PDF] [Code]
  Yixin Liu, Kaize Ding, Qinghua Lu, Fuyi Li, Leo Yu Zhang, Shirui Pan.
  Advances in Neural Information Processing Systems (NeurIPS), 2023

• PREM: A Simple Yet Effective Approach for Node-Level Graph Anomaly Detection [PDF] [Code]
  Junjun Pan*, Yixin Liu*, Yizhen Zheng*, Shirui Pan.
  IEEE International Conference on Data Mining (ICDM), 2023.

• Learning Strong Graph Neural Networks with Weak Information [PDF] [Code]
  Yixin Liu, Kaize Ding, Jianling Wang, Vincent CS Lee, Huan Liu, Shirui Pan.
  ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2023.

• Beyond Smoothing: Unsupervised Graph Representation Learning with Edge Heterophily Discriminating [PDF] [Code]
  Yixin Liu, Yizhen Zheng, Daokun Zhang, Vincent CS Lee, Shirui Pan.
  AAAI Conference on Artificial Intelligence (AAAI), 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.

• GOOD-D: On Unsupervised Graph Out-Of-Distribution Detection [PDF] [Code]
  Yixin Liu, Kaize Ding, Huan Liu, Shirui Pan.
  ACM International Conference on Web Search and Data Mining (WSDM), 2023.

• Towards unsupervised deep graph structure learning [PDF] [Code]
  Yixin Liu, Yu Zheng, Daokun Zhang, Hongxu Chen, Hao Peng, Shirui Pan.
  The Web Conference (WWW), 2022.

• ANEMONE: Graph Anomaly Detection with Multi-Scale Contrastive Learning [PDF] [Code]
  Ming Jin, Yixin Liu, Yu Zheng, Lianhua Chi, Yuan-Fang Li, and Shirui Pan.
  ACM International Conference on Information and Knowledge Management (CIKM), 2021.

Journal

• From Few-Shot to Zero-Shot: Towards Generalist Graph Anomaly Detection
  Yixin Liu, Shiyuan Li, Yu Zheng, Qingfeng Chen, Chengqi Zhang, Philip S. Yu, Shirui Pan.
  IEEE Transactions on Knowledge and Data Engineering (TKDE), 2026.

• MPHIL: Multi-Prototype Hyperspherical Invariant Learning for Graph Out-of-Distribution Generalization
  Xu Shen*, Yixin Liu*, Yili Wang, Rui Miao, Yiwei Dai, Shirui Pan, Xin Wang.
  IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2026.

• CLIP-Powered Domain Generalization and Domain Adaptation: A Comprehensive Survey
  Jindong Li, Yongguang Li, Yali Fu, Jiahong Liu, Yixin Liu, Menglin Yang, Irwin King.
  IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2026.

• Graph Neural Networks for Graphs with Heterophily: A Survey
  Xin Zheng, Yi Wang, Yixin Liu, Ming Li, Miao Zhang, Di Jin, Philip S. Yu, Shirui Pan.
  IEEE Transactions on Knowledge and Data Engineering (TKDE), 2026.

• Graph-Augmented Large Language Model Agents: Current Progress and Future Prospects
  [PDF]
  Yixin Liu, Guibin Zhang, Kun Wang, Shiyuan Li, Shirui Pan.
  IEEE Intelligent Systems, 2026.

• Uncertainty-Aware Graph Neural Networks: A Multi-Hop Evidence Fusion Approach
  [PDF] [Code]
  Qingfeng Chen, Shiyuan Li, Yixin Liu, Shirui Pan, Geoffrey Webb, Shichao Zhang.
  IEEE Transactions on Neural Networks and Learning Systems (TNNLS), 2025.

• Data‐efficient Graph Learning: Problems, Progress, and Prospects [PDF]
  Kaize Ding, Yixin Liu, Chuxu Zhang, Jianling Wang.
  AI Magazine, 2024.

• 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.

• Integrating Graphs with Large Language Models: Methods and Prospects [PDF]
  Shirui Pan, Yizhen Zheng, Yixin Liu.
  IEEE Intelligent Systems, 2023.

• Graph Self-Supervised Learning: A Survey [PDF]
  Yixin Liu, Ming Jin, Shirui Pan, Chuan Zhou, Yu Zheng, Feng Xia, Philip S. Yu.
  IEEE Transactions on Knowledge and Data Engineering (TKDE), 2022.

• Anomaly Detection in Dynamic Graphs via Transformer [PDF] [Code]
  Yixin Liu, Shirui Pan, Yu Guang Wang, Fei Xiong, Liang Wang, Qingfeng Chen, Vincent CS Lee.
  IEEE Transactions on Knowledge and Data Engineering (TKDE), 2021.

• Generative and Contrastive Self-Supervised Learning for Graph Anomaly Detection [PDF] [Code]
  Yu Zheng, Ming Jin, Yixin Liu, Lianhua Chi, Khoa T Phan, Yi-Ping Phoebe Chen.
  IEEE Transactions on Knowledge and Data Engineering (TKDE), 2021.

• Anomaly Detection on Attributed Networks via Contrastive Self-Supervised Learning [PDF] [Code]
  Yixin Liu, Zhao Li, Shirui Pan, Chen Gong, Chuan Zhou, George Karypis.
  IEEE Transactions on Neural Networks and Learning Systems (TNNLS), 2021.

• Cyclic Label Propagation for Graph Semi-supervised Learning [PDF]
  Zhao Li, Yixin Liu, Zhen Zhang, Shirui Pan, Jianliang Gao, Jiajun Bu.
  World Wide Web (WWWJ), 2021.

Tutorial

• Graph Self-Supervised Learning: Taxonomy, Frontiers, and Applications [Slides]
  Yixin Liu, Yizhen Zheng, Ming Jin, Feng Xia, Shirui Pan.
  IEEE International Joint Conference on Neural Networks (IJCNN), 2023.

Preprint

• Towards Data-centric Graph Machine Learning: Review and Outlook [PDF]
  Xin Zheng, Yixin Liu, Zhifeng Bao, Meng Fang, Xia Hu, Alan Wee-Chung Liew, Shirui Pan.
  2023.

• From Unsupervised to Few-shot Graph Anomaly Detection: A Multi-scale Contrastive Learning Approach [PDF]
  Yu Zheng, Ming Jin, Yixin Liu, Lianhua Chi, Khoa T Phan, Shirui Pan, Yi-Ping Phoebe Chen.
  2022.