X-PCR：眼科诊断中跨模态渐进式临床推理基准
X-PCR: A Benchmark for Cross-modality Progressive Clinical Reasoning in Ophthalmic Diagnosis
该基准为视觉-语言模型在眼科诊断中的渐进式推理与跨模态整合能力提供了细粒度评测协议，其六阶段推理链和六模态整合任务可直接用于诊断多模态模型在临床视觉推理中的短板。
原文依据 We introduce the Cross-Modality Progressive Clinical Reasoning (X-PCR) benchmark, the first comprehensive evaluation of MLLMs through a complete ophthalmology diagnostic workflow
摘要译文
由模型翻译 · 术语统一 · 请对照原文核对关键结论尽管多模态大语言模型（MLLMs）已取得显著进展，但其用于多模态诊断的临床推理能力仍缺乏充分检验。当前基准多基于单模态数据，无法评估临床实践所必需的渐进式推理与跨模态整合能力。我们提出跨模态渐进式临床推理（X-PCR）基准，首次通过完整的眼科诊断工作流对MLLMs进行全面评估，包含两项推理任务：1）涵盖从图像质量评估到临床决策的六阶段渐进式推理链；2）整合六种成像模态的跨模态推理任务。该基准包含26,415张图像和177,868个经专家验证的视觉问答对，整理自51个公开数据集，覆盖52种眼科疾病。对21个MLLMs的评估揭示了其在渐进式推理与跨模态整合方面的关键差距。数据集与代码：https://github.com/CVI-SZU/X-PCR。
英文原文摘要 989 字符
Despite significant progress in Multi-modal Large Language Models (MLLMs), their clinical reasoning capacity for multi-modal diagnosis remains largely unexamined. Current benchmarks, mostly single-modality data, can't evaluate progressive reasoning and cross-modal integration essential for clinical practice. We introduce the Cross-Modality Progressive Clinical Reasoning (X-PCR) benchmark, the first comprehensive evaluation of MLLMs through a complete ophthalmology diagnostic workflow, with two reasoning tasks: 1) a six-stage progressive reasoning chain spanning image quality assessment to clinical decision-making, and 2) a cross-modality reasoning task integrating six imaging modalities. The benchmark comprises 26,415 images and 177,868 expert-verified VQA pairs curated from 51 public datasets, covering 52 ophthalmic diseases. Evaluation of 21 MLLMs reveals critical gaps in progressive reasoning and cross-modal integration. Dataset and code: https://github.com/CVI-SZU/X-PCR.