RadHiera: Semantic Hierarchical Reinforcement Learning for Medical Report Generation

ArXi:2511.10065v2 Announce Type: replace Vision-language models have shown promising results in radiology report generation. However, most existing methods generate reports as flat text and do not explicitly model the semantic dependency between the Findings and Impression sections, which can lead to inconsistencies between clinical observations and diagnostic