Publications

Tutorials

1. Causal Inference with Latent Variables: Recent Advances and Future Perspectives [PDF] [Code] [Slides] [Website]
   Yaochen Zhu, Yinhan He, Jing Ma, Mengxuan Hu, Sheng Li, Jundong Li
   ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2024).

Preprint

1. Safety in Graph Machine Learning: Threats and Safeguards [PDF] [Code] [Slides]
   Song Wang, Yushun Dong, Binchi Zhang, Zihan Chen, Xingbo Fu, Yinhan He, Cong Shen, Chuxu Zhang, Nitesh V. Chawla, Jundong Li

Conference Publications

2025

1. Towards Global-level Mechanistic Interpretability: A Perspective of Modular Circuits of Large Language Models [PDF] [Code] [Slides]
   Yinhan He, Wendy Zheng, Yushun Dong, Yaochen Zhu, Chen Chen, Jundong Li (ICML 2025)

2. Energy-Based Models for Predicting Mutational Effects on Proteins [PDF] [Code] [Slides]
   Patrick Soga, Zhenyu Lei, Yinhan He, Camille L. Bilodeau, Jundong Li (SIGKDD 2025)

3. Global Graph Counterfactual Explanation: A Subgraph Mapping Approach [PDF] [Code] [Slides]
   Yinhan He, Wendy Zheng, Yaochen Zhu, Jing Ma, Saumitra Mishra, Natraj Raman, Ninghao Liu, Jundong Li (TMLR)

4. Demystify Epidemic Containment in Directed Networks: Theory and Algorithms [PDF] [Code] [Slides]
   Yinhan He, Chen Chen, Song Wang, Guanghui Min, Jundong Li
   ACM International Conference on Web Search and Data Mining (WSDM 2025).

5. Virtual Nodes Can Help: Tackling Distribution Shifts in Federated Graph Learning [PDF] [Code] [Slides]
   Xingbo Fu, Zihan Chen, Yinhan He, Song Wang, Binchi Zhang, Chen Chen, Jundong Li
   Annual AAAI Conference on Artificial Intelligence (AAAI 2025).

6. Graph Neural Networks Are More Than Filters: Revisiting and Benchmarking from A Spectral Perspective [PDF] [Code] [Slides]
   Yushun Dong, Patrick Soga, Yinhan He, Song Wang, Jundong Li
   International Conference on Learning Representations (ICLR 2025).

7. Edge Prompt Tuning for Graph Neural Networks. [PDF] [Code] [Slides]
   Xingbo Fu, Yinhan He, Jundong Li
   International Conference on Learning Representations (ICLR 2025).

2024

1. Explaining Graph Neural Networks with Large Language Models: A Counterfactual Perspective on Molecule Graphs [PDF] [Code] [Slides]
   Yinhan He, Zaiyi Zheng, Patrick Soga, Yaochen Zhu, Yushun Dong, Jundong Li
   Empirical Methods in Natural Language Processing (EMNLP 2024).

2. Causal Inference with Latent Variables: Recent Advances and Future Perspectives [PDF] [Code] [Slides]
   Yaochen Zhu, Yinhan He, Jing Ma, Mengxuan Hu, Sheng Li, Jundong Li
   ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2024 Survey Track)