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Developing automatic Math Word Problem (MWP) solvers has been an interest ofNLP researchers since the 1960s. Over the last few years, there are a growingnumber of datasets and deep learning-based methods proposed for effectivelysolving MWPs. However, most existing methods are benchmarked soly on one or twodatasets, varying in different configurations, which leads to a lack ofunified, standardized, fair, and comprehensive comparison between methods. Thispaper presents MWPToolkit, the first open-source framework for solving MWPs. InMWPToolkit, we decompose the procedure of existing MWP solvers into multiplecore components and decouple their models into highly reusable modules. We alsoprovide a hyper-parameter search function to boost the performance. In total,we implement and compare 17 MWP solvers on 4 widely-used single equationgeneration benchmarks and 2 multiple equations generation benchmarks. Thesefeatures enable our MWPToolkit to be suitable for researchers to reproduceadvanced baseline models and develop new MWP solvers quickly. Code anddocuments are available at https://github.com/LYH-YF/MWPToolkit.

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