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The problem of designing NLP solvers for math word problems (MWP) has seen sustained research activity and steady gains in the test accuracy.
Effective approaches to attention-based neural machine translation
Thang Luong, Hieu Pham, and Christopher D. Manning. 2015 · 2015
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MAWPS: A math word problem repository
Rik Koncel-Kedziorski, Subhro Roy, Aida Amini, Nate Kushman, and Hannaneh Hajishirzi. 2016 · 2016
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Pay attention to the ending:strong neural baselines for the ROC story cloze task
Zheng Cai, Lifu Tu, and Kevin Gimpel. 2017 · 2017
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Learning fine-grained expressions to solve math word problems
Danqing Huang, Shuming Shi, Chin-Yew Lin, and Jian Yin. 2017 · 2017
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Learning to solve geometry problems from natural language demonstrations in textbooks
Mrinmaya Sachan and Eric Xing. 2017 · 2017
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Attention is all you need
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Ł ukasz Kaiser, and Illia Polosukhin. 2017 · 2017
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Deep neural solver for math word problems
Yan Wang, Xiaojiang Liu, and Shuming Shi. 2017 · 2017
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Graph-to-tree learning for solving math word problems
Jipeng Zhang, Lei Wang, Roy Ka-Wei Lee, Yi Bin, Yan Wang, Jie Shao, and Ee-Peng Lim. 2020 · 2017
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Annotation artifacts in natural language inference data
Suchin Gururangan, Swabha Swayamdipta, Omer Levy, Roy Schwartz, Samuel Bowman, and Noah A. Smith. 2018 · 2018
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Hypothesis only baselines in natural language inference
Adam Poliak, Jason Naradowsky, Aparajita Haldar, Rachel Rudinger, and Benjamin Van Durme. 2018 · 2018
Cited alongside, same era.
Mapping to declarative knowledge for word problem solving
Subhro Roy and Dan Roth. 2018 · 2018
Cited alongside, same era.
MathQA: Towards interpretable math word problem solving with operation-based formalisms
Aida Amini, Saadia Gabriel, Shanchuan Lin, Rik Koncel-Kedziorski, Yejin Choi, and Hannaneh Hajishirzi. 2019 · 2019
Cited alongside, same era.
Analysis methods in neural language processing: A survey
Yonatan Belinkov and James Glass. 2019 · 2019
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Roberta: A robustly optimized bert pretraining approach
Yinhan Liu, Myle Ott, Naman Goyal, Jingfei Du, Mandar Joshi, Danqi Chen, Omer Levy, Mike Lewis, Luke Zettlemoyer, and Veselin Stoyanov. 2019 · 2019
Cited alongside, same era.
Evaluating models’ local decision boundaries via contrast sets
Matt Gardner, Yoav Artzi, Victoria Basmova, Jonathan Berant, Ben Bogin, Sihao Chen, Pradeep Dasigi, Dheeru Dua, Yanai Elazar, Ananth Gottumukkala, Nitish Gupta, Hanna Hajishirzi, Gabriel Ilharco, Daniel Khashabi, Kevin Lin, Jiangming Liu, Nelson F. Liu, Phoebe Mulcaire, Qiang Ning, Sameer Singh, Noah A. Smith, Sanjay Subramanian, Reut Tsarfaty, Eric Wallace, Ally Zhang, and Ben Zhou. 2020 · 2020
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How can we accelerate progress towards human-like linguistic generalization?
Tal Linzen. 2020 · 2020
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A diverse corpus for evaluating and developing English math word problem solvers
Shen-yun Miao, Chao-Chun Liang, and Keh-Yih Su. 2020 · 2020
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Adversarial NLI: A new benchmark for natural language understanding
Yixin Nie, Adina Williams, Emily Dinan, Mohit Bansal, Jason Weston, and Douwe Kiela. 2020 · 2020
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Semantically-aligned universal tree-structured solver for math word problems
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Right for the wrong reasons: Diagnosing syntactic heuristics in natural language inference
Tom McCoy, Ellie Pavlick, and Tal Linzen. 2019 · 2019
Cited alongside, same era.
Attention is not not explanation
Sarah Wiegreffe and Yuval Pinter. 2019 · 2019
Cited alongside, same era.
A goal-driven tree-structured neural model for math word problems
Zhipeng Xie and Shichao Sun. 2019 · 2019
Cited alongside, same era.
Roberta: A robustly optimized bert pretraining approach
Yinhan Liu, Myle Ott, Naman Goyal, Jingfei Du, Mandar Joshi, Danqi Chen, Omer Levy, Mike Lewis, Luke Zettlemoyer, and Veselin Stoyanov. 2019 · 2019
Cited alongside, same era.
How well do computers solve math word problems? large-scale dataset construction and evaluation
Danqing Huang, Shuming Shi, Chin-Yew Lin, Jian Yin, and Wei-Ying Ma. 2016a
Cited in the paper.
How well do computers solve math word problems? large-scale dataset construction and evaluation
Danqing Huang, Shuming Shi, Chin-Yew Lin, Jian Yin, and Wei-Ying Ma. 2016b
Cited in the paper.
Jinghui Qin, Lihui Lin, Xiaodan Liang, Rumin Zhang, and Liang Lin. 2020 · 2020
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Beyond accuracy: Behavioral testing of NLP models with CheckList
Marco Tulio Ribeiro, Tongshuang Wu, Carlos Guestrin, and Sameer Singh. 2020 · 2020
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Exposing Shallow Heuristics of Relation Extraction Models with Challenge Data
Shachar Rosenman, Alon Jacovi, and Yoav Goldberg. 2020 · 2020
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The gap of semantic parsing: A survey on automatic math word problem solvers
D. Zhang, L. Wang, L. Zhang, B. T. Dai, and H. T. Shen. 2020 · 2020
Later among the works it cites.
Graph-to-tree learning for solving math word problems
Jipeng Zhang, Lei Wang, Roy Ka-Wei Lee, Yi Bin, Yan Wang, Jie Shao, and Ee-Peng Lim. 2020 · 2020
Later among the works it cites.