Datasets:

ycpNotFound
/

GeoGen

language:
  - en
license: mit
size_categories:
  - 10K<n<100K
task_categories:
  - visual-question-answering
  - image-text-to-text
pretty_name: GeoExpand & GeoSynth
tags:
  - mathematical-reasoning
  - geometry-problem-solving
  - multimodal-reasoning

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.