@inproceedings{liu-etal-2023-comsearch,
title = "{C}om{S}earch: Equation Searching with Combinatorial Strategy for Solving Math Word Problems with Weak Supervision",
author = "Liu, Qianying and
Guan, Wenyu and
Shen, Jianhao and
Cheng, Fei and
Kurohashi, Sadao",
booktitle = "Proceedings of the 17th Conference of the European Chapter of the Association for Computational Linguistics",
month = may,
year = "2023",
address = "Dubrovnik, Croatia",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2023.eacl-main.186",
doi = "10.18653/v1/2023.eacl-main.186",
pages = "2549--2562",
abstract = "Previous studies have introduced a weakly-supervised paradigm for solving math word problems requiring only the answer value annotation. While these methods search for correct value equation candidates as pseudo labels, they search among a narrow sub-space of the enormous equation space. To address this problem, we propose a novel search algorithm with combinatorial strategy ComSearch, which can compress the search space by excluding mathematically equivalent equations. The compression allows the searching algorithm to enumerate all possible equations and obtain high-quality data. We investigate the noise in the pseudo labels that hold wrong mathematical logic, which we refer to as the false-matching problem, and propose a ranking model to denoise the pseudo labels. Our approach holds a flexible framework to utilize two existing supervised math word problem solvers to train pseudo labels, and both achieve state-of-the-art performance in the weak supervision task.",
}

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%0 Conference Proceedings
%T ComSearch: Equation Searching with Combinatorial Strategy for Solving Math Word Problems with Weak Supervision
%A Liu, Qianying
%A Guan, Wenyu
%A Shen, Jianhao
%A Cheng, Fei
%A Kurohashi, Sadao
%S Proceedings of the 17th Conference of the European Chapter of the Association for Computational Linguistics
%D 2023
%8 May
%I Association for Computational Linguistics
%C Dubrovnik, Croatia
%F liu-etal-2023-comsearch
%X Previous studies have introduced a weakly-supervised paradigm for solving math word problems requiring only the answer value annotation. While these methods search for correct value equation candidates as pseudo labels, they search among a narrow sub-space of the enormous equation space. To address this problem, we propose a novel search algorithm with combinatorial strategy ComSearch, which can compress the search space by excluding mathematically equivalent equations. The compression allows the searching algorithm to enumerate all possible equations and obtain high-quality data. We investigate the noise in the pseudo labels that hold wrong mathematical logic, which we refer to as the false-matching problem, and propose a ranking model to denoise the pseudo labels. Our approach holds a flexible framework to utilize two existing supervised math word problem solvers to train pseudo labels, and both achieve state-of-the-art performance in the weak supervision task.
%R 10.18653/v1/2023.eacl-main.186
%U https://aclanthology.org/2023.eacl-main.186
%U https://doi.org/10.18653/v1/2023.eacl-main.186
%P 2549-2562

##### Markdown (Informal)

[ComSearch: Equation Searching with Combinatorial Strategy for Solving Math Word Problems with Weak Supervision](https://aclanthology.org/2023.eacl-main.186) (Liu et al., EACL 2023)

##### ACL