Author

Xiandong Li

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#artificial intelligence May 2026

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

Experiments show that C-MIG outperforms RAGRL baselines in and out of domain and stays competitive with far larger medical-specialist and general-purpose LLMs, at only about 3.4% training overhead and no inference-time cost.

Yu-Wei Miao, Gen Li, Yunsheng Zeng et al. · arXiv.org · 0 citations

Preprint Aug 2026

G-CARL: Grounded Checklist-Aligned Reward Learning for Patient-Oriented Medical Report Interpretation

G-CARL, a grounded, checklist-aligned reinforcement learning framework that combines multi-source retrieval for atomic claim verification with context-aware, instance-specific weighted checklists for response coverage, providing structured supervision for factuality, user-demand satisfaction, and expression quality wit...

Shiao Xie, Siyu Chen, Jian-Wei Lv et al. · 0 citations