SafeMed-R1: Advancing Medical Reasoning with Adversarial Reinforcement Learning in Vision-Language Models

This ArXiv paper explores the use of adversarial reinforcement learning to improve the generalizability and robustness of vision-language models for medical reasoning. The research focuses on enhancing the reliability of AI in healthcare applications, addressing crucial aspects of safety and accuracy.

• •The research employs adversarial reinforcement learning to boost model performance.
• •The goal is to improve the reliability and safety of AI in medical diagnosis.
• •The project targets improving the generalizability of vision-language models.