Benchmark

PathMCQA

healthcare vision multimodal reasoning multimodal

PathMMU is a massive multimodal expert-level benchmark for understanding and reasoning in pathology, containing 33,428 multimodal multi-choice questions and 24,067 images validated by seven pathologists. It evaluates Large Multimodal Models (LMMs) performance on pathology tasks, with the top-performing model GPT-4V achieving only 49.8% zero-shot performance compared to 71.8% for human pathologists.

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数据说明

分数为 0-100 百分制综合成绩(Elo 榜为相对评分,仅供同榜内比较)。评测分数属事实数据,整理自公开评测体系与厂商公开资料,部分分数为厂商自报口径,不同榜单的评测方法与数据集可能存在差异,请结合多个榜单交叉参考。

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