Sitemap
A list of all the posts and pages found on the site. For you robots out there is an XML version available for digesting as well.
Pages
Posts
Code BreakDown - MCTS in LLM
Published:
Re-implementation of rStar MCTS
Daily Dose of Large Language Models
Published:
Update LLM paper everyday!
portfolio
Portfolio item number 1
Short description of portfolio item number 1
Portfolio item number 2
Short description of portfolio item number 2
publications
An empirical study on google research football multi-agent scenarios
Published on Machine Intelligence Research, Volume 21, pages 549–570, (2024), 2024
Yan Song, He Jiang, Zheng Tian, Haifeng Zhang, Yingping Zhang, Jiangcheng Zhu, Zonghong Dai, Weinan Zhang & Jun Wang
TaxAI: A Dynamic Economic Simulator and Benchmark for Multi-Agent Reinforcement Learning
Published on AAMAS 2024, 2024
Qirui Mi, Siyu Xia, Yan Song, Haifeng Zhang, Shenghao Zhu, Jun Wang
Recommended citation: Mi, Q., Xia, S., Song, Y., Zhang, H., Zhu, S., & Wang, J. (2024). TaxAI: A Dynamic Economic Simulator and Benchmark for Multi-Agent Reinforcement Learning. Proceedings of the International Conference on Autonomous Agents and Multi-Agent Systems (AAMAS).
Download Paper
Boosting Studies of Multi-Agent Reinforcement Learning on Google Research Football Environment: the Past, Present, and Future
Published on AAMAS, 2024
Yan Song*, He Jiang*, Haifeng Zhang, Zhen Tian, Weinan Zhang, Jun Wang
AI-Olympics: Exploring the Generalization of Agents through Open Competitions
Published on IJCAI Demo, 2024
Chen Wang, Yan Song, Shuai Wu, Sa Wu, Ruizhi Zhang, Shu Lin, Haifeng Zhang
OpenR: An Open Source Framework for Advanced Reasoning with Large Language Models
Released on Arxiv, 2024
Jun Wang, Meng Fang, Ziyu Wan, Muning Wen, Jiachen Zhu, Anjie Liu, Ziqin Gong, Yan Song, Lei Chen, Lionel M. Ni, Linyi Yang, Ying Wen, Weinan Zhang
Natural Language Reinforcement Learning
Submitted on arXiv preprint, 2024
Xidong Feng, Bo Liu, Yan Song, Haotian Fu, Ziyu Wan, Girish A. Koushik, Zhiyuan Hu, Mengyue Yang, Ying Wen, Jun Wang
Recommended citation: Feng, X., Liu, B., Song, Y., Fu, H., Wan, Z., Koushik, G. A., Hu, Z., Yang, M., Wen, Y., & Wang, J. (2024). Natural Language Reinforcement Learning. arXiv preprint arXiv:2411.14251.
Download Paper
Efficient Reinforcement Learning with Large Language Model Priors
Published on ICLR 2025, 2025
Xue Yan, Yan Song, Xidong Feng, Mengyue Yang, Haifeng Zhang, Haitham Bou Ammar, Jun Wang
Recommended citation: Yan, X., Song, Y., Feng, X., Yang, M., Zhang, H., Bou Ammar, H., & Wang, J. (2025). Efficient Reinforcement Learning with Large Language Model Priors. International Conference on Learning Representations (ICLR).
Download Paper
Ask more, know better: Reinforce-Learned Prompt Questions for Decision Making with Large Language Models
Published on ECML-PKDD 2025, 2025
Xue Yan, Yan Song, Xinyu Cui, Filippos Christianos, Haifeng Zhang, David Henry Mguni, Jun Wang
Recommended citation: Yan, X., Song, Y., Cui, X., Christianos, F., Zhang, H., Mguni, D. H., & Wang, J. (2025). Ask more, know better: Reinforce-Learned Prompt Questions for Decision Making with Large Language Models. European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML-PKDD).
Download Paper
ThinkBench: Dynamic Out-of-Distribution Evaluation for Robust LLM Reasoning
Published on NeurIPS 2025 Datasets & Benchmarks Track, 2025
Shulin Huang, Linyi Yang, Yan Song, Shuang Chen, Leyang Cui, Ziyu Wan,Qingcheng Zeng, Ying Wen, Kun Shao, Weinan Zhang, Jun Wang, Yue Zhang
REMA: Learning to Meta-Think for LLMS with Multi-Agent Reinforcement Learning
Published on NeurIPS 2025, 2025
Ziyu Wan, Yunxiang LI, Xiaoyu Wen, Yan Song, Hanjing Wang, Linyi Yang, Mark Schmidt, Jun Wang, Weinan Zhang, Shuyue Hu, Ying Wen
Recommended citation: Wan, Z., LI, Y., Wen, X., Song, Y., Wang, H., Yang, L., Schmidt, M., Wang, J., Zhang, W., Hu, S., & Wen, Y. (2025). REMA: Learning to Meta-Think for LLMS with Multi-Agent Reinforcement Learning. Advances in Neural Information Processing Systems (NeurIPS).
Download Paper
talks
Talk 1 on Relevant Topic in Your Field
Published:
This is a description of your talk, which is a markdown files that can be all markdown-ified like any other post. Yay markdown!
Conference Proceeding talk 3 on Relevant Topic in Your Field
Published:
This is a description of your conference proceedings talk, note the different field in type. You can put anything in this field.