Towards Better Aligned LLM Judges for Radiology Report Evaluation across Modalities and Anatomies
Current work on radiology report evaluation has focused primarily on LLM-based metrics for chest X-rays (CXR), leaving open whether such approaches remain robust across other modalities and anatomies, and which model and prompt configurations are best suited to serve as LLM judges. We present a comprehensive evaluation of LLM judges for radiology report evaluation across diverse model families, prompting strategies, and adaptation methods, leveraging two expert-annotated datasets that span multiple imaging modalities and anatomical regions. Specifically, we compare four existing metrics (RadFact, GREEN, FineRadScore, and CRIMSON) with our proposed metric, VERT, across open- and closed-sou...
| Authors | Federica Bologna, Jean-Philippe Corbeil, Matthew Wilkens et al. |
|---|---|
| Primary category | cs.AI |
| Published | 3 April 2026 |
| Last updated at source | 14 October 2026 |
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