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


  • Yihuai Lan Xihua University
  • Lei Wang Singapore Management University
  • Qiyuan Zhang Singapore Management University
  • Yunshi Lan East China Normal University
  • Bing Tian Dai Singapore Management University
  • Yan Wang Tencent AI Lab
  • Dongxiang Zhang Zhejiang University
  • Ee-Peng Lim Singapore Management University



Math Word Problem Solving, Deep Learning, Toolkit


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




How to Cite

Lan, Y., Wang, L., Zhang, Q., Lan, Y., Dai, B. T., Wang, Y., Zhang, D., & Lim, E.-P. (2022). MWPToolkit: An Open-Source Framework for Deep Learning-Based Math Word Problem Solvers. Proceedings of the AAAI Conference on Artificial Intelligence, 36(11), 13188-13190.