Yijun Tian
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现招收 2027 Fall 入学的硕士生（7 名）、博士生（1 名），诚挚欢迎有意向从事前沿 AI 研究的同学与我联系。 Email: meetyijun@gmail.com / Google Scholar |
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Selected Publications (Google Scholar) |
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ALDEN: Reinforcement Learning for Active Navigation and Evidence Gathering in Long Documents
Tianyu Yang, Terry Ruas, Yijun Tian, Jan Philip Wahle, Daniel Kurzawe, Bela Gipp ACL 2026 (Oral) Paper / Code |
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Reinforcement Learning for Self-Improving Agent with Skill Library
Jiongxiao Wang, Qiaojing Yan, Yawei Wang, Yijun Tian, Soumya Smruti Mishra, Zhichao Xu, Megha Gandhi, Panpan Xu, Lin Lee Cheong ACL 2026 (Oral) Paper / Code |
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Graph is a Substrate Across Data Modalities
Ziming Li, Xiaoming Wu, Zehong Wang, Jiazheng Li, Yijun Tian, Jinhe Bi, Yunpu Ma, Yanfang Ye, Chuxu Zhang ICML 2026 Paper / Code |
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Rethinking On-policy Optimization for Query Augmentation
Zhichao Xu, Shengyao Zhuang, Xueguang Ma, Bingsen Chen, Yijun Tian, Fengran Mo, Tao Li, Jie Cao, Vivek Srikumar TMLR 2026 Paper / Code |
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Reinforcement Mid-Training
Yijun Tian, Shaoyu Chen, Zhichao Xu, Yawei Wang, Jinhe Bi, Peng Han, Wei Wang ICLR 2026 Paper / Code |
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Knowledge Distillation on Graphs: A Survey
Yijun Tian, Shichao Pei, Xiangliang Zhang, Chuxu Zhang, Nitesh V. Chawla ACM Computing Surveys Paper |
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Beyond Answers: Transferring Reasoning Capabilities to Smaller LLMs Using Multi-Teacher Knowledge Distillation
Yijun Tian, Yikun Han, Xiusi Chen, Wei Wang, Nitesh V. Chawla WSDM 2025 (Oral) Paper / Code |
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G-Retriever: Retrieval-Augmented Generation for Textual Graph Understanding and Question Answering
Xiaoxin He, Yijun Tian, Yifei Sun, Nitesh V. Chawla, Thomas Laurent, Yann LeCun, Xavier Bresson, Bryan Hooi NeurIPS 2024 Paper / Code |
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Democratizing Large Language Models via Personalized Parameter-Efficient Fine-tuning
Zhaoxuan Tan, Qingkai Zeng, Yijun Tian, Zheyuan Liu, Bing Yin, Meng Jiang EMNLP 2024 Paper / Code |
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Towards Safer Large Language Models through Machine Unlearning
Zheyuan Liu, Guangyao Dou, Zhaoxuan Tan, Yijun Tian, Meng Jiang ACL 2024 Paper / Code |
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S3GCL: Spectral, Swift, Spatial Graph Contrastive Learning
Guancheng Wan, Yijun Tian, Wenke Huang, Nitesh V. Chawla, Mang Ye ICML 2024 Paper / Code |
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Learning to Predict Mutational Effects of Protein-Protein Interactions by Microenvironment-aware Hierarchical Prompt Learning
Lirong Wu, Yijun Tian, Haitao Lin, Yufei Huang, Siyuan Li, Nitesh V. Chawla, Stan Z. Li ICML 2024 Paper / Code |
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MAPE-PPI: Towards Effective and Efficient Protein-Protein Interaction Prediction via Microenvironment-Aware Protein Embedding
Lirong Wu, Yijun Tian, Yufei Huang, Siyuan Li, Haitao Lin, Nitesh V. Chawla, Stan Z. Li ICLR 2024 (Spotlight) Paper / Code |
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Mitigating Emergent Robustness Degradation while Scaling Graph Learning
Xiangchi Yuan, Chunhui Zhang, Yijun Tian, Yanfang Ye, Chuxu Zhang ICLR 2024 Paper / Code |
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Graph Neural Prompting with Large Language Models
Yijun Tian, Huan Song, Zichen Wang, Haozhu Wang, Ziqing Hu, Fang Wang, Nitesh V. Chawla, Panpan Xu AAAI 2024 Paper / Code |
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Chasing All-Round Graph Representation Robustness: Model, Training, and Optimization
Chunhui Zhang, Yijun Tian, Mingxuan Ju, Zheyuan Liu, Yanfang Ye, Nitesh V. Chawla, Chuxu Zhang ICLR 2023 Paper / Code |
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Learning MLPs on Graphs: A Unified View of Effectiveness, Robustness, and Efficiency
Yijun Tian, Chuxu Zhang, Zhichun Guo, Xiangliang Zhang, Nitesh V. Chawla ICLR 2023 (Spotlight) Paper / Code |
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Heterogeneous Graph Masked Autoencoders
Yijun Tian, Kaiwen Dong, Chunhui Zhang, Chuxu Zhang, Nitesh V. Chawla AAAI 2023 (Oral) Paper / Code |
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Last updated: June 2026 |