X-PCR: A Benchmark for Cross-modality Progressive Clinical Reasoning in Ophthalmic Diagnosis
arXiv cs.CV / 4/23/2026
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Key Points
- The paper introduces X-PCR, a new benchmark to evaluate how well multi-modal large language models (MLLMs) perform progressive clinical reasoning for ophthalmic diagnosis across a full workflow.
- X-PCR includes two reasoning tasks: a six-stage progressive reasoning chain (from image quality assessment to clinical decision-making) and a cross-modality task that integrates six imaging modalities.
- The benchmark contains 26,415 images and 177,868 expert-verified VQA pairs covering 52 ophthalmic diseases, curated from 51 public datasets.
- Testing 21 MLLMs shows notable deficiencies in both progressive reasoning and cross-modal integration, indicating important gaps before clinical-ready deployment.
- The dataset and code are released publicly via the provided GitHub repository, enabling reproducible research and further benchmarking.
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