# MathQA: Towards Interpretable Math Word Problem Solving with Operation-Based Formalisms

@article{Amini2019MathQATI, title={MathQA: Towards Interpretable Math Word Problem Solving with Operation-Based Formalisms}, author={Aida Amini and Saadia Gabriel and Shanchuan Lin and Rik Koncel-Kedziorski and Yejin Choi and Hannaneh Hajishirzi}, journal={ArXiv}, year={2019}, volume={abs/1905.13319} }

We introduce a large-scale dataset of math word problems and an interpretable neural math problem solver that learns to map problems to operation programs. [... ] Key Method We additionally introduce a neural sequence-to-program model enhanced with automatic problem categorization. Our experiments show improvements over competitive baselines in our MathQA as well as the AQuA dataset. The results are still significantly lower than human performance indicating that the dataset poses new challenges for future… Expand

## 94 Citations

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