Publications
Below is a list of my publications. * denotes equal contribution, and ✉ denotes corresponding author. For a complete list, please visit my Google Scholar.
Conference
- How Attackers Launder Funds through Mixers: Characterization and Detection on Ethereum
Qishuang Fu, Hang Zheng, Xihan Xiong, Joseph Liu, Yixin Liu, Shirui Pan, Qin Wang, Weiqing Wang, Zhipeng Wang, Tsz Hon Yuen.
ACM SIGMETRICS International Conference on Measurement and Modeling of Computer Systems (SIGMETRICS), 2027.
- AtlasULP: Domain-aware Universal Link Prediction via Relation Atlas
Yujing Liu, Yixin Liu, Yu Zheng, Lianhua Chi, Alan Wee-Chung Liew, Heng Tao Shen, Shirui Pan.
Advances in Neural Information Processing Systems (NeurIPS), 2026.
Towards Generalist Graph-Level Anomaly Detection
Junjun Pan, Yixin Liu, Yu Zheng, Fuyi Li, Alan Wee-Chung Liew, Shirui Pan.
Advances in Neural Information Processing Systems (NeurIPS), 2026.DynHD: Hallucination Detection for Diffusion Large Language Models via Denoising Dynamics Deviation Learning
Yanyu Qian, Yue Tan, Yixin Liu✉, Wang Yu, Shirui Pan.
Findings of the Association for Computational Linguistics: EMNLP (Findings of EMNLP), 2026.SAIGuard: Communication-State Simulation for Proactive Defense of LLM Multi-Agent Systems
Ruxue Shi, Yili Wang, Mengnan Du, Qinggang Zhang, Rui Miao, Yixin Liu, Xin Wang.
Findings of the Association for Computational Linguistics: EMNLP (Findings of EMNLP), 2026.DiFA: Dual Evidence Fusion and Aggregation for Token-Level Text Anomaly Detection
Yanyu Qian, Pengcheng Weng, Yue Tan✉, Enguang Zuo, Yu Zheng, Yixin Liu✉.
IEEE International Conference on Data Mining (ICDM), 2026.SIM: Subspace Interaction-based Method for Token-Level Text Anomaly Detection
Kehan Yan, Yue Tan, Qingfeng Chen✉, Shiyuan Li, Yu Zheng, Yixin Liu✉.
IEEE International Conference on Data Mining (ICDM), 2026.PaSta: Noisy Node Classification with Partial Label Learning
Yujing Liu, Yixin Liu, Yu Zheng, Yue Tan, Alan Wee-Chung Liew, Shirui Pan.
IEEE International Conference on Data Mining (ICDM), 2026.HOPE: Heterophily-Aware Open-Set Node Classification with Pseudo-Extrapolation
Yumeng Dai, Yue Tan, Yixin Liu, Chenxu Wang, Pinghui Wang, Tao Qin.
IEEE International Conference on Data Mining (ICDM), 2026.FlowShield: Cryptocurrency Anti-Money Laundering with Transaction Semantics Parsing and Fund Flow Tracking
Qishuang Fu, Andreas Deppeler, Joseph K. Liu, Yixin Liu, Shirui Pan, Qin Wang, Weiqing Wang, Tsz Hon Yuen.
IEEE International Conference on Data Mining (ICDM), 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.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.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
Shiyuan Li*, Yixin Liu*, Yu Zheng, Mei Li, Quoc Viet Hung Nguyen, Shirui Pan.
ACM Web Conference (WWW), 2026.Assemble Your Crew: Automatic Multi-Agent Communication Topology Design via Autoregressive Graph Generation
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
Junjun Pan, Yixin Liu, Chuan Zhou, Fei Xiong, Alan Wee-Chung Liew, Shirui Pan.
AAAI Conference on Artificial Intelligence (AAAI), 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.Unifying Unsupervised Graph-level Anomaly Detection and Out-of-distribution Detection: A Benchmark
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.Understanding the Information Propagation Effects of Communication Topologies in LLM-based Multi-Agent Systems
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.FreeGAD: A Training-Free yet Effective Approach for Graph Anomaly Detection
Yunfeng Zhao*, Yixin Liu*, Shiyuan Li*, Qingfeng Chen, Yu Zheng, Shirui Pan.
ACM International Conference on Information and Knowledge Management (CIKM), 2025.A Label-free Heterophily-guided Approach for Unsupervised Graph Fraud Detection
Junjun Pan, Yixin Liu, Xin Zheng, Yizhen Zheng, Alan Wee-Chung Liew, Fuyi Li, Shirui Pan.
AAAI Conference on Artificial Intelligence (AAAI), 2025.SpecG: A Spectral-based Framework for Effective Graph Pre-training and Knowledge Transfer
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.A Survey of Generalization of Graph Anomaly Detection: From Transfer Learning to Foundation Models
Junjun Pan, Yu Zheng, Yue Tan, Yixin Liu✉.
International Conference on Knowledge Graph (ICKG), 2025.ARC: A Generalist Graph Anomaly Detector with In-Context Learning
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
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
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 against Label Noise
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
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
Yixin Liu, Kaize Ding, Qinghua Lu, Fuyi Li, Leo Yu Zhang, Shirui Pan.
Advances in Neural Information Processing Systems (NeurIPS), 2023.Learning Strong Graph Neural Networks with Weak Information
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
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
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
Yixin Liu, Kaize Ding, Huan Liu, Shirui Pan.
ACM International Conference on Web Search and Data Mining (WSDM), 2023.PREM: A Simple Yet Effective Approach for Node-Level Graph Anomaly Detection
Junjun Pan*, Yixin Liu*, Yizhen Zheng*, Shirui Pan.
IEEE International Conference on Data Mining (ICDM), 2023.Towards Unsupervised Deep Graph Structure Learning
Yixin Liu, Yu Zheng, Daokun Zhang, Hongxu Chen, Hao Peng, Shirui Pan.
ACM Web Conference (WWW), 2022.ANEMONE: Graph Anomaly Detection with Multi-Scale Contrastive Learning
Ming Jin, Yixin Liu, Yu Zheng, Lianhua Chi, Yuan-Fang Li, Shirui Pan.
ACM International Conference on Information and Knowledge Management (CIKM), 2021.The Multiple Classification Method of Signal Recognition for Spacecraft Based on SAE Network
Wei Lan, Yixin Liu, Zhang Qi, Shimin Song, Chun He, Lijing Wang, Ke Li.
International Conference on Man-Machine-Environment System Engineering, 2018.
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
Yixin Liu, Guibin Zhang, Kun Wang, Shiyuan Li, Shirui Pan.
IEEE Intelligent Systems, 2026.Enhancing Weak Raman Spectral Fingerprints for Multi-Source Walnut Oil Adulteration Using Multi-Level Feature Fusion [Paper]
Xinyu Bi, Zhaohui Qiao, Yuchen Ni, Feilong Yue, Min Li, Xiaoyi Lv, Enguang Zuo✉, Yixin Liu✉.
Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy, 2026.FSFDLLM: Financial Statement Fraud Detection Aided by Large Language Models
Yumeng Dai, Yanyu Qian, Xiaoguang Wang, Yixin Liu, Chenxu Wang.
Intelligent Computing, 2026.From Unsupervised to Few-shot Graph Anomaly Detection: A Multi-scale Contrastive Learning Approach
Yu Zheng, Junjun Pan, Yue Tan, Ming Jin, Yixin Liu✉, Lianhua Chi✉, Khoa T. Phan, Shirui Pan, Yi-Ping Phoebe Chen.
Transactions on Graph Intelligence and Network Applications (TGINA), 2026.Uncertainty-Aware Graph Neural Networks: A Multi-Hop Evidence Fusion Approach
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
Kaize Ding, Yixin Liu, Chuxu Zhang, Jianling Wang.
AI Magazine, 2024.Integrating Graphs with Large Language Models: Methods and Prospects
Shirui Pan, Yizhen Zheng, Yixin Liu.
IEEE Intelligent Systems, 2024.Emerging Trends in Federated Learning: From Model Fusion to Federated X Learning
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.Graph Self-Supervised Learning: A Survey
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 on Attributed Networks via Contrastive Self-Supervised Learning
Yixin Liu, Zhao Li, Shirui Pan, Chen Gong, Chuan Zhou, George Karypis.
IEEE Transactions on Neural Networks and Learning Systems (TNNLS), 2022.Cyclic Label Propagation for Graph Semi-supervised Learning
Zhao Li, Yixin Liu, Zhen Zhang, Shirui Pan, Jianliang Gao, Jiajun Bu.
World Wide Web, 2022.Anomaly Detection in Dynamic Graphs via Transformer
Yixin Liu, Shirui Pan, Yu Guang Wang, Fei Xiong, Liang Wang, Vincent Lee.
IEEE Transactions on Knowledge and Data Engineering (TKDE), 2021.Generative and Contrastive Self-Supervised Learning for Graph Anomaly Detection
Yu Zheng, Ming Jin, Yixin Liu, Lianhua Chi, Khoa T Phan, Yi-Ping Phoebe Chen.
IEEE Transactions on Knowledge and Data Engineering (TKDE), 2021.MRD-NETS: Multi-Scale Residual Networks with Dilated Convolutions for Classification and Clustering Analysis of Spacecraft Electrical Signal
Yixin Liu, Ke Li, Yuxiang Zhang, Shimin Song.
IEEE Access, 2019.A Novel Method of Hyperspectral Data Classification Based on Transfer Learning and Deep Belief Network
Ke Li, Mingju Wang, Yixin Liu, Nan Yu, Wei Lan.
Applied Sciences, 2019.
Tutorial
Graph Self-Supervised Learning: Taxonomy, Frontiers, and Applications
Yixin Liu, Yizhen Zheng, Shirui Pan.
International Conference on Advanced Data Mining and Applications (ADMA), Sydney, Australia, 2024.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), Gold Coast, Australia, 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.