Publications

(* indicates equal contribution)

1. Federated Graph Learning with Graphless Clients. [PDF]
   Xingbo Fu, Song Wang, Yushun Dong, Binchi Zhang, Chen Chen, Jundong Li.
   Transactions on Machine Learning Research (TMLR), 2024.

2. Understanding and Modeling Job Marketplace with Pretrained Language Models. [PDF]
   Yaochen Zhu, Liang Wu, Binchi Zhang, Song Wang, Qi Guo, Liangjie Hong, Luke Simon, Jundong Li.
   ACM International Conference on Information and Knowledge Management (CIKM), Applied Research Paper, 2024.

3. IDEA: A Flexible Framework of Certified Unlearning for Graph Neural Networks. [PDF] [Code]
   Yushun Dong, Binchi Zhang, Zhenyu Lei, Na Zou, Jundong Li.
   ACM SIGKDD Conference on Knowledge Discovery & Data Mining (KDD), 2024.

4. Federated Graph Learning with Structure Proxy Alignment. [PDF] [Code]
   Xingbo Fu, Zihan Chen, Binchi Zhang, Chen Chen, Jundong Li.
   ACM SIGKDD Conference on Knowledge Discovery & Data Mining (KDD), 2024.

5. Verification of Machine Unlearning is Fragile. [PDF] [Code]
   Binchi Zhang, Zihan Chen, Cong Shen, Jundong Li.
   International Conference on Machine Learning (ICML), 2024.

6. Towards Certified Unlearning for Deep Neural Networks. [PDF] [Code]
   Binchi Zhang, Yushun Dong, Tianhao Wang, Jundong Li.
   International Conference on Machine Learning (ICML), 2024.

7. Adversarial Attacks on Fairness of Graph Neural Networks. [PDF] [Code]
   Binchi Zhang, Yushun Dong, Chen Chen, Yada Zhu, Minnan Luo, Jundong Li.
   International Conference on Learning Representations (ICLR), 2024.

8. AHEAD: A Triple Attention Based Heterogeneous Graph Anomaly Detection Approach. [PDF] [Code]
   Shujie Yang, Binchi Zhang, Shangbin Feng, Zhaoxuan Tan, Qinghua Zheng, Ziqi Liu, Minnan Luo.
   Chinese Intelligent Automation Conference (CIAC), 2023 (Best Application Paper Finalist).

9. RELIANT: Fair Knowledge Distillation for Graph Neural Networks. [PDF] [Code]
   Yushun Dong, Binchi Zhang, Yiling Yuan, Na Zou, Qi Wang, Jundong Li.
   SIAM International Conference on Data Mining (SDM), 2023.

10. TwiBot-22: Towards Graph-Based Twitter Bot Detection. [PDF] [Code]
    Shangbin Feng*, Zhaoxuan Tan*, Herun Wan*, Ningnan Wang*, Zilong Chen*, Binchi Zhang*, Qinghua Zheng, Wenqian Zhang, Zhenyu Lei, Shujie Yang, Xinshun Feng, Qingyue Zhang, Hongrui Wang, Yuhan Liu, Yuyang Bai, Heng Wang, Zijian Cai, Yanbo Wang, Lijing Zheng, Zihan Ma, Jundong Li, Minnan Luo.
    Advances in Neural Information Processing Systems (NeurIPS), Datasets and Benchmarks Track, 2022.

11. Federated Graph Machine Learning: A Survey of Concepts, Techniques, and Applications. [PDF]
    Xingbo Fu, Binchi Zhang, Yushun Dong, Chen Chen, Jundong Li.
    SIGKDD Explorations Newsletter, 2022, 24(2): 32-47.
    A short version is accepted to FedGraph @ CIKM 2022 (spotlight).

12. Safety in Graph Machine Learning: Threats and Safeguards. [PDF]
    Song Wang, Yushun Dong, Binchi Zhang, Zihan Chen, Xingbo Fu, Yinhan He, Cong Shen, Chuxu Zhang, Nitesh V. Chawla, Jundong Li.
    ArXiv preprint arXiv:2405.11034, 2024.

13. ELEGANT: Certified Defense on the Fairness of Graph Neural Networks. [PDF] [Code]
    Yushun Dong, Binchi Zhang, Hanghang Tong, Jundong Li.
    ArXiv preprint arXiv:2311.02757, 2023.

14. Tackling the Local Bias in Federated Graph Learning. [PDF] [Code]
    Binchi Zhang, Minnan Luo, Shangbin Feng, Ziqi Liu, Jun Zhou, Qinghua Zheng.
    ArXiv preprint arXiv:2110.12906, 2021.