Datasets:
File size: 1,278 Bytes
6a36632 4779672 6a36632 4779672 37bf318 4779672 37bf318 4779672 37bf318 4779672 90c9b1c 4779672 37bf318 4779672 37bf318 4779672 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 |
---
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](https://arxiv.org/pdf/2504.12773).
The datasets are designed to enhance and evaluate the geometric problem-solving capabilities of multimodal large language models.
GitHub Repository: [ycpNotFound/GeoGen](https://github.com/ycpNotFound/GeoGen)
These datasets are also referenced and contextualized in the survey paper [A Survey of Deep Learning for Geometry Problem Solving](https://huggingface.co/papers/2507.11936), which provides a comprehensive overview of the field. The survey's reading list is maintained on its GitHub repository: [majianz/gps-survey](https://github.com/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. |