| 2026 | WSDM | MolEdit: Knowledge Editing for Multimodal Molecule Language Models. | Zhenyu Lei, Patrick Soga, Yaochen Zhu, Yinhan He, Yushun Dong, Jundong Li |
| 2025 | AAAI | Virtual Nodes Can Help: Tackling Distribution Shifts in Federated Graph Learning. | Xingbo Fu, Zihan Chen, Yinhan He, Song Wang, Binchi Zhang, Chen Chen, Jundong Li |
| 2025 | EMNLP | CoRAG: Enhancing Hybrid Retrieval-Augmented Generation through a Cooperative Retriever Architecture. | Zaiyi Zheng, Song Wang, Zihan Chen, Yaochen Zhu, Yinhan He, Liangjie Hong, Qi Guo, Jundong Li |
| 2025 | EMNLP | LLM-based Conversational Recommendation Agents with Collaborative Verbalized Experience. | Yaochen Zhu, Harald Steck, Dawen Liang, Yinhan He, Nathan Kallus, Jundong Li |
| 2025 | ICLR | Graph Neural Networks Are More Than Filters: Revisiting and Benchmarking from A Spectral Perspective. | Yushun Dong, Patrick Soga, Yinhan He, Song Wang, Jundong Li |
| 2025 | ICLR | Edge Prompt Tuning for Graph Neural Networks. | Xingbo Fu, Yinhan He, Jundong Li |
| 2025 | ICML | Towards Global-level Mechanistic Interpretability: A Perspective of Modular Circuits of Large Language Models. | Yinhan He, Wendy Zheng, Yushun Dong, Yaochen Zhu, Chen Chen, Jundong Li |
| 2025 | KDD | Energy-Based Models for Predicting Mutational Effects on Proteins. | Patrick Soga, Zhenyu Lei, Yinhan He, Camille L. Bilodeau, Jundong Li |
| 2025 | WSDM | Demystify Epidemic Containment in Directed Networks: Theory and Algorithms. | Yinhan He, Chen Chen, Song Wang, Guanghui Min, Jundong Li |
| 2024 | EMNLP | Explaining Graph Neural Networks with Large Language Models: A Counterfactual Perspective on Molecule Graphs. | Yinhan He, Zaiyi Zheng, Patrick Soga, Yaochen Zhu, Yushun Dong, Jundong Li |
| 2024 | KDD | Causal Inference with Latent Variables: Recent Advances and Future Prospectives. | Yaochen Zhu, Yinhan He, Jing Ma, Mengxuan Hu, Sheng Li, Jundong Li |