@inproceedings{wang-etal-2017-deep,
title = "Deep Neural Solver for Math Word Problems",
author = "Wang, Yan and
Liu, Xiaojiang and
Shi, Shuming",
booktitle = "Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing",
month = sep,
year = "2017",
address = "Copenhagen, Denmark",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/D17-1088",
doi = "10.18653/v1/D17-1088",
pages = "845--854",
abstract = "This paper presents a deep neural solver to automatically solve math word problems. In contrast to previous statistical learning approaches, we directly translate math word problems to equation templates using a recurrent neural network (RNN) model, without sophisticated feature engineering. We further design a hybrid model that combines the RNN model and a similarity-based retrieval model to achieve additional performance improvement. Experiments conducted on a large dataset show that the RNN model and the hybrid model significantly outperform state-of-the-art statistical learning methods for math word problem solving.",
}

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%0 Conference Proceedings
%T Deep Neural Solver for Math Word Problems
%A Wang, Yan
%A Liu, Xiaojiang
%A Shi, Shuming
%S Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing
%D 2017
%8 September
%I Association for Computational Linguistics
%C Copenhagen, Denmark
%F wang-etal-2017-deep
%X This paper presents a deep neural solver to automatically solve math word problems. In contrast to previous statistical learning approaches, we directly translate math word problems to equation templates using a recurrent neural network (RNN) model, without sophisticated feature engineering. We further design a hybrid model that combines the RNN model and a similarity-based retrieval model to achieve additional performance improvement. Experiments conducted on a large dataset show that the RNN model and the hybrid model significantly outperform state-of-the-art statistical learning methods for math word problem solving.
%R 10.18653/v1/D17-1088
%U https://aclanthology.org/D17-1088
%U https://doi.org/10.18653/v1/D17-1088
%P 845-854

##### Markdown (Informal)

[Deep Neural Solver for Math Word Problems](https://aclanthology.org/D17-1088) (Wang et al., EMNLP 2017)

##### ACL

- Yan Wang, Xiaojiang Liu, and Shuming Shi. 2017. Deep Neural Solver for Math Word Problems. In
*Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing*, pages 845–854, Copenhagen, Denmark. Association for Computational Linguistics.