---
license: afl-3.0
---
# MWP-BERT
NAACL 2022 Findings Paper: MWP-BERT: Numeracy-Augmented Pre-training for Math Word Problem Solving

[![PWC](https://img.shields.io/endpoint.svg?url=https://paperswithcode.com/badge/mwp-bert-a-strong-baseline-for-math-word/math-word-problem-solving-on-mathqa)](https://paperswithcode.com/sota/math-word-problem-solving-on-mathqa?p=mwp-bert-a-strong-baseline-for-math-word)
[![PWC](https://img.shields.io/endpoint.svg?url=https://paperswithcode.com/badge/mwp-bert-a-strong-baseline-for-math-word/math-word-problem-solving-on-math23k)](https://paperswithcode.com/sota/math-word-problem-solving-on-math23k?p=mwp-bert-a-strong-baseline-for-math-word)

Github link: https://github.com/LZhenwen/MWP-BERT/


Please use the tokenizer of "hfl/chinese-bert-wwm-ext" for this model.

## Citation

```
@inproceedings{liang2022mwp,
  title={MWP-BERT: Numeracy-Augmented Pre-training for Math Word Problem Solving},
  author={Liang, Zhenwen and Zhang, Jipeng and Wang, Lei and Qin, Wei and Lan, Yunshi and Shao, Jie and Zhang, Xiangliang},
  booktitle={Findings of NAACL 2022},
  pages={997--1009},
  year={2022}
}
```