C-MIG: Multi-view Information Gain-based Retrieval-Augmented Generation for Clinical Diagnosis Reasoning

In three linesC-MIG introduces a multi-view information gain-based RAG framework for clinical diagnosis reasoning. It replaces exact-match binary rewards with information gain estimation from two views (retrieved documents and document refinement) to better supervise LLM reasoning. Experiments on four medical benchmarks show improvements over RAG-RL baselines in both in-domain and out-of-domain settings.

Summary generated by Claude — human-verified