MWPToolkit: An Open-Source Framework for Deep Learning-Based Math Word Problem Solvers

48Citations
Citations of this article
48Readers
Mendeley users who have this article in their library.

Abstract

While Math Word Problem (MWP) solving has emerged as a popular field of study and made great progress in recent years, most existing methods are benchmarked solely on one or two datasets and implemented with different configurations. In this paper, we introduce the first open-source library for solving MWPs called MWPToolkit, which provides a unified, comprehensive, and extensible framework for the research purpose. Specifically, we deploy 17 deep learning-based MWP solvers and 6 MWP datasets in our toolkit. These MWP solvers are advanced models for MWP solving, covering the categories of Seq2seq, Seq2Tree, Graph2Tree, and Pre-trained Language Models. And these MWP datasets are popular datasets that are commonly used as benchmarks in existing work. Our toolkit is featured with highly modularized and reusable components, which can help researchers quickly get started and develop their own models. We have released the code and documentation of MWPToolkit in https://github.com/LYH-YF/MWPToolkit.

Cite

CITATION STYLE

APA

Lan, Y., Wang, L., Zhang, Q., Lan, Y., Dai, B. T., Wang, Y., … Lim, E. P. (2022). MWPToolkit: An Open-Source Framework for Deep Learning-Based Math Word Problem Solvers. In Proceedings of the 36th AAAI Conference on Artificial Intelligence, AAAI 2022 (Vol. 36, pp. 13188–13190). Association for the Advancement of Artificial Intelligence. https://doi.org/10.1609/aaai.v36i11.21723

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free