📝 Selected Research Papers

🎙 Graph Machine Learning

• ICAIF 2025 Robust Graph Learning in Finance, Xiang Ao, Yang Liu, Guansong Pang, Yuanhao Ding, Hezhe Qiao, Dawei Cheng, and Qing He.
• ICDM 2025 Dilution of Unreliable Information: Learning in Graph with Noisy Structures and Absent Attributes, Xinxin Li, Yang Liu, Weigao Wen, Siyong Xu, Qing He, and Xiang Ao.
• KDD 2025 GRASP: Differentially Private Graph Reconstruction Defense with Structured Perturbation, Zhiyu Guo, Yang Liu, Xiang Ao, Qing He.
• WWW 2025 SPEAR: A Structure-Preserving Manipulation Method for Graph Backdoor Attacks, Yuanhao Ding, Yang Liu, Yugang Ji, Weigao Wen, Qing He and Xiang Ao.
• WWW 2025 Panoramic Interests: Stylistic-Content Aware Personalized Headline Generation, Junhong Lian, Xiang Ao, Xinyu Liu, Yang Liu and Qing He.
• AAAI 2025 Dynamic Graph Learning with Static Relations for Credit Risk Assessment, Qi Yuan, Yang Liu, Yateng Tang, Xinhuan Chen, Xuehao Zheng, Qing He and Xiang Ao.
• DASFAA 2025 OFTEN: Graph Invariant Learning via Soft Environment Inference, Yang Liu, Zikun Zhang, Xiang Ao, Lingxiang Tian, Qing He.
• ICASSP 2025 Domain-aware Node Representation Learning for Graph Out-of-Distribution Generalization, Yi Qiao, Yang Liu, Qing He, Xiang Ao.
• WSDM 2025 LOGIN: A Large Language Model Consulted Graph Neural Network Training Framework, Yiran Qiao, Xiang Ao, Yang Liu, Jiarong Xu, Xiaoqian Sun and Qing He.
• ICLR 2024 Boosting the Adversarial Robustness of Graph Neural Networks: An OOD Perspective, Kuan Li, Yiwen Chen, Yang Liu, Jin Wang, Qing He, Minhao Cheng and Xiang Ao.
• ICLR 2023 Revisiting Graph Adversarial Attack and Defense From a Data Distribution Perspective, Kuan Li, Yang Liu, Xiang Ao, Qing He.
• KDD 2023 FLOOD: A Flexible Invariant Learning Framework for Out-of-Distribution Generalization on Graphs, Yang Liu, Xiang Ao, Fuli Feng, Yunshan Ma, Kuan Li, Tat-Seng Chua and Qing He.
• KDD 2022 UD-GNN: Uncertainty-aware Debiased Training on Semi-Homophilous Graphs, Yang Liu, Xiang Ao, Fuli Feng, and Qing He.
• WWW 2021 Pick and Choose: A GNN-based Imbalanced Learning Approach for Fraud Detection, Yang Liu, Xiang Ao, Zidi Qin, Jianfeng Chi, Jinghua Feng, Hao Yang and Qing He. Slides Talk
• CIKM 2020 Alike and Unlike: Resolving Class Imbalance Problem in Financial Credit Risk Assessment, Yang Liu, Xiang Ao, Qiwei Zhong, Jinghua Feng, Jiayu Tang, and Qing He. Slides Talk Proceedings of the 29th ACM International Conference on Information and Knowledge Management (CIKM), 2020.