Abstract
We introduce a new type of problems for math word problem (MWP) solvers, named Noun-MWPs, whose answer is a non-numerical string containing a noun from the problem text. We present a novel method to empower existing MWP solvers to handle Noun-MWPs, and apply the method on Expression-Pointer Transformer (EPT). Our model, N-EPT, solves Noun-MWPs significantly better than other models, and at the same time, solves conventional MWPs as well. Solving Noun-MWPs may lead to bridging MWP solvers and traditional question-answering NLP models.- Anthology ID:
- 2022.coling-1.338
- Original:
- 2022.coling-1.338v1
- Version 2:
- 2022.coling-1.338v2
- Volume:
- Proceedings of the 29th International Conference on Computational Linguistics
- Month:
- October
- Year:
- 2022
- Address:
- Gyeongju, Republic of Korea
- Editors:
- Nicoletta Calzolari, Chu-Ren Huang, Hansaem Kim, James Pustejovsky, Leo Wanner, Key-Sun Choi, Pum-Mo Ryu, Hsin-Hsi Chen, Lucia Donatelli, Heng Ji, Sadao Kurohashi, Patrizia Paggio, Nianwen Xue, Seokhwan Kim, Younggyun Hahm, Zhong He, Tony Kyungil Lee, Enrico Santus, Francis Bond, Seung-Hoon Na
- Venue:
- COLING
- SIG:
- Publisher:
- International Committee on Computational Linguistics
- Note:
- Pages:
- 3847–3857
- Language:
- URL:
- https://aclanthology.org/2022.coling-1.338
- DOI:
- Bibkey:
- Cite (ACL):
- Taehun Cha, Jaeheun Jung, and Donghun Lee. 2022. Noun-MWP: Math Word Problems Meet Noun Answers. In Proceedings of the 29th International Conference on Computational Linguistics, pages 3847–3857, Gyeongju, Republic of Korea. International Committee on Computational Linguistics.
- Cite (Informal):
- Noun-MWP: Math Word Problems Meet Noun Answers (Cha et al., COLING 2022)
- Copy Citation:
- PDF:
- https://aclanthology.org/2022.coling-1.338.pdf
- Data
- ASDiv, MAWPS
Export citation
@inproceedings{cha-etal-2022-noun, title = "Noun-{MWP}: Math Word Problems Meet Noun Answers", author = "Cha, Taehun and Jung, Jaeheun and Lee, Donghun", editor = "Calzolari, Nicoletta and Huang, Chu-Ren and Kim, Hansaem and Pustejovsky, James and Wanner, Leo and Choi, Key-Sun and Ryu, Pum-Mo and Chen, Hsin-Hsi and Donatelli, Lucia and Ji, Heng and Kurohashi, Sadao and Paggio, Patrizia and Xue, Nianwen and Kim, Seokhwan and Hahm, Younggyun and He, Zhong and Lee, Tony Kyungil and Santus, Enrico and Bond, Francis and Na, Seung-Hoon", booktitle = "Proceedings of the 29th International Conference on Computational Linguistics", month = oct, year = "2022", address = "Gyeongju, Republic of Korea", publisher = "International Committee on Computational Linguistics", url = "https://aclanthology.org/2022.coling-1.338", pages = "3847--3857", abstract = "We introduce a new type of problems for math word problem (MWP) solvers, named Noun-MWPs, whose answer is a non-numerical string containing a noun from the problem text. We present a novel method to empower existing MWP solvers to handle Noun-MWPs, and apply the method on Expression-Pointer Transformer (EPT). Our model, N-EPT, solves Noun-MWPs significantly better than other models, and at the same time, solves conventional MWPs as well. Solving Noun-MWPs may lead to bridging MWP solvers and traditional question-answering NLP models.", }
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%0 Conference Proceedings %T Noun-MWP: Math Word Problems Meet Noun Answers %A Cha, Taehun %A Jung, Jaeheun %A Lee, Donghun %Y Calzolari, Nicoletta %Y Huang, Chu-Ren %Y Kim, Hansaem %Y Pustejovsky, James %Y Wanner, Leo %Y Choi, Key-Sun %Y Ryu, Pum-Mo %Y Chen, Hsin-Hsi %Y Donatelli, Lucia %Y Ji, Heng %Y Kurohashi, Sadao %Y Paggio, Patrizia %Y Xue, Nianwen %Y Kim, Seokhwan %Y Hahm, Younggyun %Y He, Zhong %Y Lee, Tony Kyungil %Y Santus, Enrico %Y Bond, Francis %Y Na, Seung-Hoon %S Proceedings of the 29th International Conference on Computational Linguistics %D 2022 %8 October %I International Committee on Computational Linguistics %C Gyeongju, Republic of Korea %F cha-etal-2022-noun %X We introduce a new type of problems for math word problem (MWP) solvers, named Noun-MWPs, whose answer is a non-numerical string containing a noun from the problem text. We present a novel method to empower existing MWP solvers to handle Noun-MWPs, and apply the method on Expression-Pointer Transformer (EPT). Our model, N-EPT, solves Noun-MWPs significantly better than other models, and at the same time, solves conventional MWPs as well. Solving Noun-MWPs may lead to bridging MWP solvers and traditional question-answering NLP models. %U https://aclanthology.org/2022.coling-1.338 %P 3847-3857
Markdown (Informal)
[Noun-MWP: Math Word Problems Meet Noun Answers](https://aclanthology.org/2022.coling-1.338) (Cha et al., COLING 2022)
- Noun-MWP: Math Word Problems Meet Noun Answers (Cha et al., COLING 2022)
ACL
- Taehun Cha, Jaeheun Jung, and Donghun Lee. 2022. Noun-MWP: Math Word Problems Meet Noun Answers. In Proceedings of the 29th International Conference on Computational Linguistics, pages 3847–3857, Gyeongju, Republic of Korea. International Committee on Computational Linguistics.