Publication Type

Conference Proceeding Article

Version

acceptedVersion

Publication Date

3-2022

Abstract

Duplicate record, see https://ink.library.smu.edu.sg/sis_research/7680/. Developing automatic Math Word Problem (MWP) solvers has been an interest of NLP researchers since the 1960s. Over the last few years, there are a growing number of datasets and deep learning-based methods proposed for effectively solving MWPs. However, most existing methods are benchmarked solely on one or two datasets, varying in different configurations, which leads to a lack of unified, standardized, fair, and comprehensive comparison between methods. This paper presents MWPToolkit, the first open-source framework for solving MWPs. In MWPToolkit, we decompose the procedure of existing MWP solvers into multiple core components and decouple their models into highly reusable modules. We also provide a hyper-parameter search function to boost the performance. In total, we implement and compare 17 MWP solvers on 4 widely-used single equation generation benchmarks and 2 multiple equations generation benchmarks. These features enable our MWPToolkit to be suitable for researchers to reproduce advanced baseline models and develop new MWP solvers quickly.

Discipline

Databases and Information Systems

Research Areas

Data Science and Engineering

Publication

Proceedings of the 36th AAAI Conference on Artificial Intelligence, Virtual Conference, 2022 February 22 - March 1

First Page

13188

Last Page

13190

Identifier

10.1609/aaai.v36i11.21723

Publisher

AAAI

City or Country

Palo Alto, CA

Copyright Owner and License

Publisher

Additional URL

https://doi.org/10.1609/aaai.v36i11.21723

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