Abstract
This paper investigates the question of what makes math word problems (MWPs) in English challenging for large language models (LLMs). We conduct an in-depth analysis of the key linguistic and mathematical characteristics of MWPs. In addition, we train feature-based classifiers to better understand the impact of each feature on the overall difficulty of MWPs for prominent LLMs and investigate whether this helps predict how well LLMs fare against specific categories of MWPs.- Anthology ID:
- 2024.findings-naacl.72
- Volume:
- Findings of the Association for Computational Linguistics: NAACL 2024
- Month:
- June
- Year:
- 2024
- Address:
- Mexico City, Mexico
- Editors:
- Kevin Duh, Helena Gomez, Steven Bethard
- Venue:
- Findings
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 1138–1148
- Language:
- URL:
- https://aclanthology.org/2024.findings-naacl.72
- DOI:
- Cite (ACL):
- Kv Aditya Srivatsa and Ekaterina Kochmar. 2024. What Makes Math Word Problems Challenging for LLMs?. In Findings of the Association for Computational Linguistics: NAACL 2024, pages 1138–1148, Mexico City, Mexico. Association for Computational Linguistics.
- Cite (Informal):
- What Makes Math Word Problems Challenging for LLMs? (Srivatsa & Kochmar, Findings 2024)
- PDF:
- https://preview.aclanthology.org/naacl24-info/2024.findings-naacl.72.pdf