Datasets:

ecnu-icalk
/

cmm-math

language:
  - en
license: mit
task_categories:
  - image-text-to-text
tags:
  - survey
  - mathematical-reasoning
  - geometry
  - deep-learning
  - reading-list
  - multimodal
  - literature-review

Deep Learning for Geometry Problem Solving (DL4GPS) Survey

This repository serves as a continuously updated reading list for the paper:

Paper: A Survey of Deep Learning for Geometry Problem Solving GitHub Repository: https://github.com/majianz/gps-survey

Abstract

Geometry problem solving is a key area of mathematical reasoning, which is widely involved in many important fields such as education, mathematical ability assessment of artificial intelligence, and multimodal ability assessment. In recent years, the rapid development of deep learning technology, especially the rise of multimodal large language models, has triggered a widespread research boom. This paper provides a survey of the applications of deep learning in geometry problem solving, including (i) a comprehensive summary of the relevant tasks in geometry problem solving; (ii) a thorough review of related deep learning methods; (iii) a detailed analysis of evaluation metrics and methods; and (iv) a critical discussion of the current challenges and future directions that can be explored. Our goal is to provide a comprehensive and practical reference of deep learning for geometry problem solving to promote further developments in this field. We create a continuously updated list of papers on GitHub.

Overview and Content

This GitHub repository accompanies the survey paper and provides a dynamic reading list on Deep Learning for Geometry Problem Solving (DL4GPS). It is continuously updated and aims to provide a comprehensive reference for the field.

The content is organized into the following main sections:

Surveys: Related surveys on mathematical reasoning and deep learning.
Tasks and Datasets - Fundamental Tasks:
- Geometry Problem Parsing (Semantic Parsing, Geometric Diagram Parsing)
- Geometry Problem Understanding (Geometric Diagram Understanding, Geometric Relation Extraction, Geometric Knowledge Prediction)
Tasks and Datasets - Core Tasks:
- Geometry Theorem Proving
- Geometric Numerical Calculation

 **Tasks and Datasets - Composite Tasks:**

Mathematical Reasoning
Multimodal Perception

Tasks and Datasets - Other Geometry Tasks:
- Geometric Diagram Generation (Reconstruction, Text-to-Diagram)
- Geometric Construction Problem
- Geometric Diagram Retrieval
- Geometric Autoformalization
Architectures
Methods
Related Surveys

For detailed categorization and direct links to papers, please refer to the GitHub repository. The current deadline for included papers in the GitHub list is April 2025.

If you have any suggestions or notice something we missed, please don't hesitate to let us know. You can directly email Jianzhe Ma (majianzhe@ruc.edu.cn), or post an issue on the GitHub repository.

Citation

If you find this survey and reading list useful for your research, please cite the original paper:

@misc{deeplearninggeometrysurvey,
  title={A Survey of Deep Learning for Geometry Problem Solving},
  year={2025},
  note={Available at https://huggingface.co/papers/2507.11936}
}