A Survey of Deep Learning for Geometry Problem Solving
It addresses the need for improved AI capabilities in mathematical reasoning and multimodal tasks, but is incremental as it is a survey paper.
This paper surveys the application of deep learning, including multimodal large language models, to geometry problem solving, summarizing tasks, methods, evaluation metrics, challenges, and future directions to provide a comprehensive reference for advancing the field.
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 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 objective is to offer a comprehensive and practical reference of deep learning for geometry problem solving, thereby fostering further advancements in this field. We create a continuously updated list of papers on GitHub: https://github.com/majianz/dl4gps.