Publications
Tutorials
- 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
- 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 - Rank-GRPO: Training LLM-based Conversational Recommender Systems with Reinforcement Learning [PDF] [Code] [Slides]
Yaochen Zhu, Harald Steck, Dawen Liang, Yinhan He, Jundong Li, Nathan Kallus
Conference Publications
2025
MolEdit: Knowledge Editing for Multimodal Molecule Language Models [PDF] [Code] [Slides]
Zhenyu Lei, Patrick Soga, Yaochen Zhu, Yinhan He, Yushun Dong and Jundong Li (WSDM 2026)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)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)Scaling Epidemic Inference on Contact Networks: Theory and Algorithms [PDF] [Code] [Slides]
Guanghui Min, Yinhan He, Chen Chen (NeurIPS 2025)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)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)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)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)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)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)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).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).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).Edge Prompt Tuning for Graph Neural Networks. [PDF] [Code] [Slides]
Xingbo Fu, Yinhan He, Jundong Li
International Conference on Learning Representations (ICLR 2025).
2024
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).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)