Math Word Problem

Math word problem (MWP) solving aims to automatically translate natural language descriptions into mathematical equations and solutions, a crucial step towards more robust AI systems. Current research heavily utilizes large language models (LLMs), often enhanced with techniques like chain-of-thought prompting, to improve accuracy and address challenges such as handling irrelevant information and longer problem contexts. This field is significant because effective MWP solvers have broad applications in education, automated assessment, and other areas requiring natural language understanding and mathematical reasoning; ongoing work focuses on improving model robustness, interpretability, and the ability to handle diverse problem types and complexities.