Date
Publisher
arXiv
Geometry problem solving, a crucial aspect of mathematical reasoning, is vital across various domains, including education, the assessment of AI's mathematical abilities, and multimodal capability evaluation. The recent surge in deep learning technologies, particularly the emergence of multimodal large language models, has significantly accelerated research in this area. This paper presents 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 state-of-the-art performance, existing challenges, and promising future directions. Our objective is to offer a comprehensive and practical reference of deep learning for geometry problem solving, thereby fostering further advancements in this field. We maintain a list of relevant papers: https://github.com/majianz/dl4gps.
Key findings
- Across the studies reviewed in education, multimodal large language models have significantly accelerated research into automated geometry problem solving.
- Geometry problem solving serves as a vital indicator of mathematical reasoning across educational domains and multimodal artificial intelligence evaluations.
- Top-performing deep learning methods continue to face ongoing challenges when attempting to solve geometry problems.
Summary drafted with AI from the paper’s abstract and may contain errors. See the full paper for details.
Why use AI?
Study design
