license: apache-2.0
library_name: transformers
pipeline_tag: text-generation
MedAgentGym: Training LLM Agents for Code-Based Medical Reasoning at Scale
The model was presented in the paper MedAgentGym: Training LLM Agents for Code-Based Medical Reasoning at Scale.
Paper abstract
We introduce MedAgentGYM, the first publicly available training environment designed to enhance coding-based medical reasoning capabilities in large language model (LLM) agents. MedAgentGYM comprises 72,413 task instances across 129 categories derived from authentic real-world biomedical scenarios. Tasks are encapsulated within executable coding environments, each featuring detailed task descriptions, interactive feedback mechanisms, verifiable ground-truth annotations, and scalable training trajectory generation. Extensive benchmarking of over 30 LLMs reveals a notable performance disparity between commercial API-based models and open-source counterparts. Leveraging MedAgentGYM, Med-Copilot-7B achieves substantial performance gains through supervised fine-tuning (+36.44%) and continued reinforcement learning (+42.47%), emerging as an affordable and privacy-preserving alternative competitive with gpt-4o. By offering both a comprehensive benchmark and accessible, expandable training resources within unified execution environments, MedAgentGYM delivers an integrated platform to develop LLM-based coding assistants for advanced biomedical research and practice.
Project page: https://huggingface.co/MedAgentGym
Code: https://github.com/MedAgentGym/MedAgentGym (Please replace with the actual link if different)