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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
Ask more, know better: Reinforce-Learned Prompt Questions for Decision Making with Large Language Models
Released on Arxiv, 2024
Xue Yan, Yan Song, Xinyu Cui, Filippos Christianos, Haifeng Zhang, David Henry Mguni, Jun Wang
TaxAI: A Dynamic Economic Simulator and Benchmark for Multi-Agent Reinforcement Learning
Published on AAMAS, 2024
Qirui Mi, Siyu Xia, Yan Song, Haifeng Zhang, Shenghao Zhu, Jun Wang
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
Efficient Reinforcement Learning with Large Language Model Priors
Published on ICLR, 2025
Xue Yan, Yan Song, Xidong Feng, Mengyue Yang, Haifeng Zhang, Haitham Bou Ammar, Jun Wang
ThinkBench: Dynamic Out-of-Distribution Evaluation for Robust LLM Reasoning
Released on Arxiv, 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
Released on Arxiv, 2025
Ziyu Wan, Yunxiang Li, Yan Song, Hanjing Wang, Linyi Yang, Mark Schmidt, Jun Wang, Weinan Zhang, Shuyue Hu, Ying Wen
talks
Talk 1 on Relevant Topic in Your Field
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Conference Proceeding talk 3 on Relevant Topic in Your Field
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