CV

Education

• Ph.D in Version Control Theory, GitHub University, 2018 (expected)
• M.S. in Jekyll, GitHub University, 2014
• B.S. in GitHub, GitHub University, 2012

Work experience

• Spring 2024: Academic Pages Collaborator
  • Github University
  • Duties includes: Updates and improvements to template
  • Supervisor: The Users
• Fall 2015: Research Assistant
  • Github University
  • Duties included: Merging pull requests
  • Supervisor: Professor Hub
• Summer 2015: Research Assistant
  • Github University
  • Duties included: Tagging issues
  • Supervisor: Professor Git

Skills

• Skill 1
• Skill 2
  • Sub-skill 2.1
  • Sub-skill 2.2
  • Sub-skill 2.3
• Skill 3

Publications

Memory-Driven Self-Improvement for Decision Making with Large Language Models

REMA: Learning to Meta-Think for LLMS with Multi-Agent Reinforcement Learning

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).

ThinkBench: Dynamic Out-of-Distribution Evaluation for Robust LLM Reasoning

Ask more, know better: Reinforce-Learned Prompt Questions for Decision Making with Large Language Models

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).

Efficient Reinforcement Learning with Large Language Model Priors

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).

Natural Language Reinforcement Learning

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.

OpenR: An Open Source Framework for Advanced Reasoning with Large Language Models

AI-Olympics: Exploring the Generalization of Agents through Open Competitions

Boosting Studies of Multi-Agent Reinforcement Learning on Google Research Football Environment: the Past, Present, and Future

TaxAI: A Dynamic Economic Simulator and Benchmark for Multi-Agent Reinforcement Learning

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).

An empirical study on google research football multi-agent scenarios

Talks

Conference Proceeding talk 3 on Relevant Topic in Your Field

March 01, 2014

Conference proceedings talk at Testing Institute of America 2014 Annual Conference, Los Angeles, CA

Talk 2 on Relevant Topic in Your Field

February 01, 2014

Talk at London School of Testing, London, UK

Tutorial 1 on Relevant Topic in Your Field

March 01, 2013

Tutorial at UC-Berkeley Institute for Testing Science, Berkeley CA, USA

Talk 1 on Relevant Topic in Your Field

March 01, 2012

Talk at UC San Francisco, Department of Testing, San Francisco, California

Teaching

Service and leadership

• Currently signed in to 43 different slack teams