AI RESEARCH
CWCD: Category-Wise Contrastive Decoding for Structured Medical Report Generation
arXiv CS.AI
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ArXi:2604.10410v1 Announce Type: new Interpreting chest X-rays is inherently challenging due to the overlap between anatomical structures and the subtle presentation of many clinically significant pathologies, making accurate diagnosis time-consuming even for experienced radiologists. Recent radiology-focused foundation models, such as LLaVA-Rad and Maira-2, have positioned multi-modal large language models (MLLMs) at the forefront of automated radiology report generation (RRG). However, despite these advances, current foundation models generate reports in a single forward pass.