AlgoPuzzleVQA
Harbor: pendingWe introduce the novel task of multimodal puzzle solving, framed within the context of visual question-answering.
- Samples
- 1,800
- Released
- 2024
- Scores
- 1
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.
$ npm i -g lettokenburn-cli$ ltb bench info mathverse
External harness. No Harbor adapter has been generated for this benchmark yet. `ltb bench info` prints the known links.
Runs happen on your machine with your own subscription; only the score summary is pushed. CLI docs
No sourced scores recorded yet.
Every number links to where it was published. Low-confidence rows are muted and need per-cell verification.
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.