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. Hierarchical Demonstration Order Optimization for Many-shot In-Context Learning [PDF] [Code] [Slides]
   Yinhan He, Wendy Zheng, Song Wang, Zaiyi Zheng, Yushun Dong, Yaochen Zhu, Jundong Li (NeurIPS 2025)

2. SemCoT: Accelerating Chain-of-Thought Reasoning through Semantically-Aligned Implicit Tokens [PDF] [Code] [Slides]
   Yinhan He, Wendy Zheng, Yaochen Zhu, Zaiyi Zheng, Lin Su, Sriram Vasudevan, Qi Guo, Liangjie Hong, Jundong Li (NeurIPS 2025)

3. Scaling Epidemic Inference on Contact Networks: Theory and Algorithms [PDF] [Code] [Slides]
   Guanghui Min, Yinhan He, Chen Chen (NeurIPS 2025)

4. LM-based Conversational Recommendation Agents with Collaborative Verbalized Experience [PDF] [Code] [Slides]
   Yaochen Zhu, Harald Steck, Dawen Liang, Yinhan He, Nathan Kallus, Jundong Li (EMNLP 2025)

5. CoRAG: Enhancing Hybrid Retrieval-Augmented Generation through a Cooperative Retriever Architecture [PDF] [Code] [Slides]
   Zaiyi Zheng, Song Wang, Zihan Chen, Yaochen Zhu, Yinhan He, Liangjie Hong, Qi Guo, Jundong Li (EMNLP 2025)

6. LM-based Conversational Recommendation Agents with Collaborative Verbalized Experience [PDF] [Code] [Slides]
   Yaochen Zhu, Harald Steck, Dawen Liang, Yinhan He, Nathan Kallus, Jundong Li (GenAIRegP)

7. 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)

8. 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)

9. 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)

10. 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).

11. 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).

12. 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).

13. 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)