Abstract
In recent years, math word problem solving has received considerable attention and achieved promising results, but previous methods rarely take numerical values into consideration. Most methods treat the numerical values in the problems as number symbols, and ignore the prominent role of the numerical values in solving the problem. In this paper, we propose a novel approach called NumS2T, which enhances math word problem solving performance by explicitly incorporating numerical values into a sequence-to-tree network. In addition, a numerical properties prediction mechanism is used to capture the category and comparison information of numerals and measure their importance in global expressions. Experimental results on the Math23K and APE datasets demonstrate that our model achieves better performance than existing state-of-the-art models.- Anthology ID:
- 2021.acl-long.455
- Volume:
- Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (Volume 1: Long Papers)
- Month:
- August
- Year:
- 2021
- Address:
- Online
- Venues:
- ACL | IJCNLP
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 5859–5869
- Language:
- URL:
- https://aclanthology.org/2021.acl-long.455
- DOI:
- 10.18653/v1/2021.acl-long.455
- Cite (ACL):
- Qinzhuo Wu, Qi Zhang, Zhongyu Wei, and Xuanjing Huang. 2021. Math Word Problem Solving with Explicit Numerical Values. In Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (Volume 1: Long Papers), pages 5859–5869, Online. Association for Computational Linguistics.
- Cite (Informal):
- Math Word Problem Solving with Explicit Numerical Values (Wu et al., ACL-IJCNLP 2021)
- PDF:
- https://preview.aclanthology.org/ingestion-script-update/2021.acl-long.455.pdf
- Code
- qinzhuowu/nums2t
- Data
- Math23K