😀    About Me

I am a researcher at the Multi-Agent System Lab, Beijing Institute for General Artificial Intelligence. My research interests include multi-agent systems, reinforcement learning, large language models, and spatio-temporal data mining.

I received my Ph.D. in Computer Science and Engineering from the Hong Kong University of Science and Technology under the supervision of Prof. Qiang Yang and Dr. Yu Zheng. My work has been published in top-tier conferences such as ICML, ICLR, ACL, KDD, WWW, AAAI, and CIKM, as well as leading journals including TKDE, Transportation Research Part C.

Hiring PhD students jointly supervised with 上海交通大学 北京理工大学 上海科技大学
- An interest in Multi-agent systems & Large language models & Data mining
- Strong code ability
- Determination to do high-quality research

🔥    News

📝    Selected Publications

# equal contribution    ‡ corresponding authors

2026

• Yexin Li. CAE: Repurposing the Critic as an Explorer in Deep Reinforcement Learning. Transactions on Machine Learning Research. TMLR 2026 forthcoming
• Zheng Zhang, Ziwei Shan, Kaitao Song, Yexin Li ^‡, Kan Ren ^‡. Linking Process to Outcome: Conditional Reward Modeling for LLM Reasoning. International Conference on Learning Representations. ICLR 2026
• Jinjin Guo, Yexin Li ^‡, Zhichao Huang, Jun Fang, Zhiyuan Liu, Chao Liu, Pengzhang Liu, Qixia Jiang. Spectral Disentanglement and Enhancement: A Dual-domain Contrastive Framework for Representation Learning. The ACM Web Conference. WWW 2026
• Sijie Ruan, Renchi Jiang, Song Tang, Yexin Li, Weixin Zhai, Xinhao Liu, Bingbing Hu, Hanning Yuan, Caicong Wu, Shuliang Wang. Predictive Mobile Refueling for Agricultural Machinery via Deep Reinforcement Learning. ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. SIGKDD 2026
• Zhixiang Zhang, Shuo Chen, Yexin Li, Feng Wang. ADAPT: Adaptive Decentralized Architecture with Perception-Aligned Training for Structural Generalization in Multi-Agent RL. Annual AAAI Conference on Artificial Intelligence. AAAI 2026

2025

• Zheng Zhang, Shaocheng Lan, Lei Song, Jiang Bian, Yexin Li, Kan Ren. Learning to Select In-Context Demonstration Preferred by Large Language Model. Annual Meeting of the Association for Computational Linguistics. ACL Findings 2025
• Yipeng Kang, Junqi Wang, Yexin Li, Mengmeng Wang, Wenming Tu, Quansen Wang, Hengli Li, Tingjun Wu, Xue Feng, Fangwei Zhong, Zilong Zheng. Are the Values of LLMs Structurally Aligned with Humans? A Causal Perspective. Annual Meeting of the Association for Computational Linguistics. ACL Findings 2025

2024

• Yexin Li, Zhancun Mu, Siyuan Qi. A Contextual Combinatorial Bandit Approach to Negotiation. International Conference on Machine Learning. ICML 2024
• Siyuan Qi ^#, Shuo Chen ^#, Yexin Li ^#, Xiangyu Kong ^#, Junqi Wang ^#, Bangcheng Yang, Pring Wong, Yifan Zhong, Xiaoyuan Zhang, Zhaowei Zhang, Nian Liu, Wei Wang, Yaodong Yang, Song-Chun Zhu. CivRealm: A Learning and Reasoning Odyssey in Civilization for Decision-Making Agents. International Conference on Learning Representations. ICLR 2024

2023 and Before

• Siyuan Feng, Shuqing Wei, Junbo Zhang, Yexin Li, Jintao Ke, Gaode Chen, Yu Zheng, Hai Yang. A Macro–Micro Spatio-temporal Neural Network for Traffic Prediction. Transportation Research Part C: Emerging Technologies. TR Part C 2023
• Tianfu He, Jie Bao, Yexin Li, Hui He, Yu Zheng. Crowd-Sensing Enhanced Parking Patrol Using Sharing Bikes’ Trajectories. IEEE Transactions on Knowledge and Data Engineering. TKDE 2021
• Yexin Li, Yu Zheng, Qiang Yang. Cooperative Multi-Agent Reinforcement Learning in Express System. ACM International Conference on Information and Knowledge Management. CIKM 2020
• Ting Li, Junbo Zhang, Kainan Bao, Yuxuan Liang, Yexin Li, Yu Zheng. AutoST: Efficient Neural Architecture Search for Spatio-temporal Prediction. ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. SIGKDD 2020
• Yexin Li, Yu Zheng, Qiang Yang. Efficient and Effective Express via Contextual Cooperative Reinforcement Learning. ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. SIGKDD 2019
• Yexin Li, Yu Zheng. Citywide Bike Usage Prediction in a Bike-Sharing System. IEEE Transactions on Knowledge and Data Engineering. TKDE 2019
• Yexin Li, Yu Zheng, Qiang Yang. Dynamic Bike Reposition: A Spatio-Temporal Reinforcement Learning Approach. ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. SIGKDD 2018
• Yexin Li, Yu Zheng, Huichu Zhang, Lei Chen. Traffic Prediction in a Bike-Sharing System. ACM International Conference on Advances in Geographical Information Systems. SIGSPATIAL 2015

🎓    Education

• 2016.09 - 2020.11 - Ph.D. in Computer Science and Engineering, Hong Kong University of Science and Technology
• 2013.09 - 2015.08 - MPhil in Computer Science and Engineering, Hong Kong University of Science and Technology
• 2009.09 - 2013.07 - B.S. in Mathematics and Applied Mathematics, Xi'an Jiaotong University

💼    Work Experience

• 2023.04 - Now - Researcher at the Multi-Agent Systems Lab, Beijing Institute for General Artificial Intelligence
• 2021.01 - 2023.03 - Doctor Management Trainee at JD.COM
• 2017.05 - 2018.01 - Research Intern at Microsoft Research Asia

🤝    Collaborators

• Shuo Chen  -   Researcher at Multi-Agent System Lab, Beijing Institute for General Artificial Intelligence
• Sijie Ruan  -   Assistant professor at School of Computer Science and Technology, Beijing Institute of Technology
• Siyuan Qi  -   Researcher at Multi-Agent System Lab, Beijing Institute for General Artificial Intelligence
• Jinjin Guo  -   Algorithm Engineer at JD.com