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MathVerse

Introduced by Renrui Zhang et al. in MathVerse: Does Your Multi-modal LLM Truly See the Diagrams in Visual Math Problems?21 Mar 2024 archive 2025-07-28

MathVerse is an innovative benchmark specifically designed to rigorously evaluate the capabilities of Multi-modal Large Language Models (MLLMs) in interpreting and reasoning with visual information in mathematical problems. Developed by a research team from CUHK MMLab and Shanghai Artificial Intelligence Laboratory, MathVerse offers an equitable and comprehensive assessment of MLLMs' ability to understand and process visual diagrams for mathematical reasoning.

The benchmark consists of 2,612 high-quality, multi-subject math problems with diagrams, meticulously collected from publicly available sources. Each problem is then transformed by human annotators into six distinct versions, each offering varying degrees of information content in multi-modality. This approach results in a total of 15K test samples, allowing MathVerse to thoroughly examine whether and how much MLLMs can genuinely comprehend visual diagrams for solving mathematical problems.

Benchmarks archive 2025-07-28

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Papers archive 2025-07-28

No paper in the archive has a leaderboard row on this dataset; the archive counts 82 papers for it but never published that list.

Dataset loaders archive 2025-07-28

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Tasks archive 2025-07-28

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License archive 2025-07-28

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Modalities archive 2025-07-28

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Languages archive 2025-07-28

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Variants archive 2025-07-28

  • MathVerse

1 variant name, as the archive lists them.

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