A Survey of Deep Learning for Geometry Problem Solving
Paper • 2507.11936 • Published • 1
Datasets:
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GeoGeo: GeoExpand & GeoSynth
This repository contains the GeoExpand and GeoSynth datasets, originally introduced in the paper Enhancing the Geometric Problem-Solving Ability of Multimodal LLMs via Symbolic-Neural Integration.
The datasets are designed to enhance and evaluate the geometric problem-solving capabilities of multimodal large language models.
GitHub Repository: ycpNotFound/GeoGen
These datasets are also referenced and contextualized in the survey paper A Survey of Deep Learning for Geometry Problem Solving, which provides a comprehensive overview of the field. The survey's reading list is maintained on its GitHub repository: majianz/gps-survey.
- GeoExpand includes 45,526 Q&A samples, generated from 4849 images in total of Geometry3K and PGPS9K.
- GeoSynth includes 62,868 Q&A samples, with one diagram for one Q&A each.
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