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Image & vision evals

MMMU

by MMMU team (OSU, Waterloo & collaborators)

About 11.5K college-level questions across six disciplines and 30 subjects, each pairing text with images such as charts, diagrams, maps and chemical structures.

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Image & vision evals

MathVista

by UCLA, University of Washington & Microsoft Research

6,141 math problems set in visual contexts, drawn from 28 existing multimodal datasets plus three new ones (IQTest, FunctionQA, PaperQA).

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Image & vision evals

MMBench

by OpenCompass (Shanghai AI Lab & collaborators)

A bilingual (English and Chinese) multiple-choice benchmark that breaks vision-language ability into fine-grained skills, with a scoring method meant to be more robust than single-pass answers.

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Image & vision evals

ChartQA

by Masry et al. (academic)

9.6K human-written and 23.1K generated questions about real charts that need visual reading plus logical and arithmetic reasoning.

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