Large Language Models for Mathematical Reasoning: Progresses and Challenges

Janice Ahn, Rishu Verma, Renze Lou, Di Liu, Rui Zhang, Wenpeng Yin


Abstract
Mathematical reasoning serves as a cornerstone for assessing the fundamental cognitive capabilities of human intelligence. In recent times, there has been a notable surge in the development of Large Language Models (LLMs) geared towards the automated resolution of mathematical problems. However, the landscape of mathematical problem types is vast and varied, with LLM-oriented techniques undergoing evaluation across diverse datasets and settings. This diversity makes it challenging to discern the true advancements and obstacles within this burgeoning field. This survey endeavors to address four pivotal dimensions: i) a comprehensive exploration of the various mathematical problems and their corresponding datasets that have been investigated; ii) an examination of the spectrum of LLM-oriented techniques that have been proposed for mathematical problem-solving; iii) an overview of factors and concerns affecting LLMs in solving math; and iv) an elucidation of the persisting challenges within this domain. To the best of our knowledge, this survey stands as one of the first extensive examinations of the landscape of LLMs in the realm of mathematics, providing a holistic perspective on the current state, accomplishments, and future challenges in this rapidly evolving field.
Anthology ID:
2024.eacl-srw.17
Volume:
Proceedings of the 18th Conference of the European Chapter of the Association for Computational Linguistics: Student Research Workshop
Month:
March
Year:
2024
Address:
St. Julian’s, Malta
Editors:
Neele Falk, Sara Papi, Mike Zhang
Venue:
EACL
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
225–237
Language:
URL:
https://aclanthology.org/2024.eacl-srw.17
DOI:
Bibkey:
Cite (ACL):
Janice Ahn, Rishu Verma, Renze Lou, Di Liu, Rui Zhang, and Wenpeng Yin. 2024. Large Language Models for Mathematical Reasoning: Progresses and Challenges. In Proceedings of the 18th Conference of the European Chapter of the Association for Computational Linguistics: Student Research Workshop, pages 225–237, St. Julian’s, Malta. Association for Computational Linguistics.
Cite (Informal):
Large Language Models for Mathematical Reasoning: Progresses and Challenges (Ahn et al., EACL 2024)
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PDF:
https://aclanthology.org/2024.eacl-srw.17.pdf
Video:
 https://aclanthology.org/2024.eacl-srw.17.mp4