Publications

More information can be found in my Google Scholar

Preprint

• Graph-MLLM: Harnessing Multimodal Large Language Models for Multimodal Graph Learning
  Jiajin Liu, Dongzhe Fan, Jiacheng Shen, Chuanhao Ji, Daochen Zha, and Qiaoyu Tan
  arXiv:2506.10282, 2025.

• MLaGA: Multimodal Large Language and Graph Assistant
  Dongzhe Fan, Yi Fang, Jiajin Liu, Djellel Difallah, and Qiaoyu Tan
  arXiv:2406.12950, 2025.

• MolecularGPT: Open Large Language Model (LLM) for Few-Shot Molecular Property Prediction
  Yuyan Liu, Sirui Ding, Sheng Zhou, Wenqi Fan, and Qiaoyu Tan
  arXiv:2406.12950, 2024.

• GraphFM: A Comprehensive Benchmark for Graph Foundation Model
  Yuhao Xu, Xinqi Liu, Keyu Duan, Yi Fang, Yu-Neng Chuang, Daochen Zha, and Qiaoyu Tan
  arXiv:2406.08310, 2024.

• ChatGraph: Interpretable Text Classification by Converting ChatGPT Knowledge to Graphs
  Yucheng Shi, Hehuan Ma, Wenliang Zhong, Qiaoyu Tan, Gengchen Mai, Xiang Li, Tianming Liu and Junzhou Huang
  arXiv:2305.03513, 2023.

• MGAE: Masked Autoencoders for Self-Supervised Learning on Graphs
  Qiaoyu Tan, Ninghao Liu, Xiao Huang, Rui Chen, Soo-Hyun Choi and Xia Hu
  arXiv:2201.02534, 2022.

Conference/Journal Publications

• CrystalICL: Enabling In-Context Learning for Crystal Generation
  Ruobing Wang, Qiaoyu Tan, Yili Wang, Ying Wang, and Xin Wang.
  Empirical Methods in Natural Language Processing (EMNLP), 2025.

• TrustGLM: Evaluating the Robustness of GraphLLMs Against Prompt, Text, and Structure Attacks
  Qihai Zhang, Xinyue Sheng, Yuanfu Sun, and Qiaoyu Tan.
  ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), 2025.

• Concept-Centric Token Interpretation for Vector-Quantized Generative Models
  Tianze Yang, Yucheng Shi, Mengnan Du, Xuansheng Wu, Qiaoyu Tan, Jin Sun, and Ninghao Liu.
  International Conference on Machine Learning (ICML), 2025.

• Towards a Unified Framework of Clustering-based Anomaly Detection
  Zeyu Fang, Ming Gu, Sheng Zhou, Jiawei Chen, Qiaoyu Tan, Haishuai Wang, and Jiajun Bu.
  International Conference on Machine Learning (ICML), 2025.

• GRAPHGPT-O: Synergistic Multimodal Comprehension and Generation on Graphs
  Yi Fang, Bowen Jin, Jiacheng Shen, Sirui Ding, Qiaoyu Tan, and Jiawei Han.
  IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2025.

• GraphICL: Unlocking Graph Learning Potential in LLMs through Structured Prompt Design
  Yuanfu Sun, Zhengnan Ma, Yi Fang, Jing Ma, and Qiaoyu Tan.
  Findings of the Nations of the Americas Chapter of the Association for Computational Linguistics (NAACL Findings), 2025.

• UniGLM: Training One Unified Language Model for Text-Attributed Graphs
  Yi Fang, Dongzhe Fan, Sirui Ding, Ninghao Liu, and Qiaoyu Tan.
  ACM International Conference on Web Search and Data Mining (WSDM), 2025.

• Gradient Rewiring for Editable Graph Neural Network Training
  Zhimeng Jiang, Zirui Liu, Xiaotian Han, Qizhang Feng, Hongye Jin, Qiaoyu Tan, Kaixiong Zhou, Na Zou, and Xia Hu.
  Neural Information Processing Systems (NeurIPS), 2024.

• Retrieval-Enhanced Knowledge Editing for Multi-Hop Question Answering in Language Models
  Yucheng Shi, Qiaoyu Tan, Xuansheng Wu, Shaochen Zhong, Kaixiong Zhou, and Ninghao Liu.
  ACM International Conference on Information and Knowledge Management (CIKM), 2024.

• GAugLLM: Improving Graph Contrastive Learning for Text-attributed Graphs with Large Language Models
  Yi Fang, Dongzhe Fan, Daochen Zha, and Qiaoyu Tan.
  ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), 2024.

• Reasoning Like a Doctor: Improving Medical Dialogue Systems via Diagnostic Reasoning Process Alignment
  Kaishuai Xu, Yi Cheng, Wenjun Hou, Qiaoyu Tan, and Wenjie Li.
  Findings of the Association for Computational Linguistics (ACL Findings), 2024.

• DIRECT: Dual Interpretable Recommendation with Multi-aspect Word Attribution
  Xuansheng Wu, Hanqin Wan, Qiaoyu Tan, Wenlin Yao and Ninghao Liu.
  ACM Transactions on Intelligent Systems and Technology (TIST), 2024.

• Graph Contrastive Learning with Personalized Augmentation
  Xin Zhang, Qiaoyu Tan, Xiao Huang and Bo Li.
  Transactions on Knowledge and Data Engineering (TKDE), 2024.

• OpenGSL: A Comprehensive Benchmark for Graph Structure Learning
  Zhiyao Zhou, Sheng Zhou, Bochao Mao, Xuanyi Zhou, jiawei Chen, Qiaoyu Tan, Daochen Zha, Can Wang, Yan Feng and Chun Chen.
  Neural Information Processing Systems Datasets and Benchmarks Track (NeurIPS), 2023.

• Double Wins: Boosting Accuracy and Efficiency of Graph Neural Networks by Reliable Knowledge Distillation
  Qiaoyu Tan, Daochen Zha, Ninghao Liu, Soo-Hyun Choi, Li Li, Rui Chen and Xia Hu.
  IEEE International Conference on Data Mining (ICDM), 2023.

• Reinforcement Neighborhood Selection for Unsupervised Graph Anomaly Detection
  Yuanchen Bei, Sheng Zhou, Qiaoyu Tan, Hao Xu, Hao Chen, Zhao Li and Jiajun Bu.
  IEEE International Conference on Data Mining (ICDM), 2023.

• Integrating Entity Attributes for Error-Aware Knowledge Graph Embedding
  Qianggang Zhang, Junnan Dong, Qiaoyu Tan and Xiao Huang.
  Transactions on Knowledge and Data Engineering (TKDE), 2023.

• GiGaMA: Generalizable Graph Masked Autoencoder via Collaborative Latent Space Reconstruction
  Yucheng Shi, Yushun Dong, Qiaoyu Tan, Jundong Li and Ninghao Liu.
  ACM International Conference on Information and Knowledge Management (CIKM), 2023.

• Homophily-enhanced Structure Learning for Graph Clustering
  Ming Gu, Gaoming Yang, Sheng Zhou, Ning Ma, Jiawei Chen, Qiaoyu Tan, Meihan Liu and Jiajun Bu.
  ACM International Conference on Information and Knowledge Management (CIKM), 2023.

• Collaborative Graph Neural Networks for Attributed Network Embedding
  Qiaoyu Tan, Xin Zhang, Xiao Huang, Hao Chen, Jundong Li and Xia Hu.
  Transactions on Knowledge and Data Engineering (TKDE), 2023.

• Multi-task Learning for Post-transplant Cause of Death Analysis
  Sirui Ding, Qiaoyu Tan, Chia-yuan Chang, Na Zou, Kai Zhang, Nathan R. Hoot, Xiaoqian Jiang and Xia Hu.
  AMIA Annual Symposium (AMIA), 2023.

• Towards Fair Patient-Trial Matching via Patient-Criterion Level Fairness Constraint
  Chia-Yuan Chang, Jiayi Yuan, Sirui Ding, Qiaoyu Tan, Kai Zhang, Xiaoqian Jiang, Xia Hu and Na Zou.
  AMIA Annual Symposium (AMIA), 2023.

• Interest Driven Graph Structure Learning for Session-based Recommendation
  Huachi Zhou, Shuang Zhou, Keyu Duan, Xiao Huang, Qiaoyu Tan and Zailiang Yu.
  The Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD), 2023.

• Hierarchy-Aware Multi-Hop Question Answering over Knowledge Graphs
  Junnan Dong, Qinggang Zhang, Xiao Huang, Keyu Duan, Qiaoyu Tan and Zhimeng Jiang.
  The Web Conference (WWW), 2023.

• S2GAE: Self-Supervised Graph Autoencoders Are Generalizable Learners with Graph Masking
  Qiaoyu Tan, Ninghao Liu, Xiao Huang, Soo-Hyun Choi, Li Li, Rui Chen and Xia Hu.
  ACM International Conference on Web Search and Data Mining (WSDM), 2023.

• Active Ensemble Learning for Knowledge Graph Error Detection
  Junnan Dong, Qinggang Zhang, Xiao Huang, Qiaoyu Tan, Daochen Zha and Zihao Zhao.
  ACM International Conference on Web Search and Data Mining (WSDM), 2023.

• Bring Your Own View: Graph Neural Networks for Link Prediction with Personalized Subgraph Selection
  Qiaoyu Tan, Xin Zhang, Ninghao Liu, Daochen Zha, Li Li, Rui Chen, Soo-Hyun Choi and Xia Hu.
  ACM International Conference on Web Search and Data Mining (WSDM), 2023.

• DreamShard: Generalizable Embedding Table Placement for Recommender Systems
  Daochen Zha, Louis Feng, Qiaoyu Tan, Zirui Liu, Kwei-Herng, Bhargav, Bhushanam, Yuandong Tian, Arun Kejariwal and Xia Hu.
  Neural Information Processing Systems (NeurIPS), 2022.

• Towards Automated Imbalanced Learning with Deep Hierarchical Reinforcement Learning
  Daochen Zha, Kwei-Herng Lai, Qiaoyu Tan, Sirui Ding, Na Zou and Xia Hu.
  ACM International Conference on Information and Knowledge Management (CIKM), 2022.

• Unseen Anomaly Detection on Networks via Multi-Hypersphere Learning
  Shuang Zhou, Xiao Huang, Ninghao Liu, Qiaoyu Tan and Fu-Lai Chung.
  SIAM International Conference on Data Mining (SDM), 2022.

• Sparse-Interest Network for Sequential Recommendation
  Qiaoyu Tan, Jianwei Zhang, Jiangchao Yao, Ninghao Liu, Jingren Zhou, Hongxia Yang and Xia Hu.
  ACM International Conference on Web Search and Data Mining (WSDM), 2021.

• Dynamic Memory based Attention Network for Sequential Recommendation
  Qiaoyu Tan, Jianwei Zhang, Ninghao Liu, Xiao Huang, Hongxia Yang, Jingren Zhou and Xia Hu.
  AAAI Conference on Artificial Intelligence (AAAI), 2021.

• Subtractive Aggregation for Attributed Anomaly Detection
  Shuang Zhou, Qiaoyu Tan, Zhiming Xu, Xiao Huang and Fu-lai Chung.
  ACM International Conference on Information and Knowledge Management (CIKM), 2021.

• Temporal Augmented Graph Neural Networks for Session-based Recommendation
  Huachi Zhou, Qiaoyu Tan, Xiao Huang, Kaixiong Zhou and Xiaoling Wang.
  ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR), 2021.

• Learning to Hash with Graph Neural Networks for Recommender Systems
  Qiaoyu Tan, Ninghao Liu, Xing Zhao, Hongxia Yang, Jingren Zhou and Xia Hu.
  The Web Conference (WWW), 2020.

• Is a Single Vector Enough? Exploring Node Polysemy for Network Embedding
  Ninghao Liu, Qiaoyu Tan, Yuening Li, Hongxia Yang, Jingren Zhou and Xia Hu.
  ACM SIGKDD International Conference on Knowledge Discovery & Data Mining (KDD), 2019.

• Deep Representation Learning for Social Network Analysis
  Qiaoyu Tan, Ninghao Liu and Xia Hu.
  Frontiers in Big Data), 2019.

• Individual and Commonality based Multi-View Multi-Label Learning
  Qiaoyu Tan, Guoxian Yu, Jun Wang, Carlotta Domeniconi and Xiangliang Zhang.
  IEEE Transactions on Cybernetics (IEEE Trans Cybern), 2019.

• Incomplete Multi-View Weak-Label Learning
  Qiaoyu Tan, Guoxian Yu, Carlotta Domeniconi, Jun Wang and Zili Zhang.
  International Joint Conference on Artificial Intelligence (IJCAI), 2018.

• Multi-View Weak-Label based on Matrix Completion
  Qiaoyu Tan, Guoxian Yu, Carlotta Domeniconi, Jun Wang and Zili Zhang.
  SIAM International Conference on Data Mining (SDM), 2018.