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Mathematical reasoning is regarded as a necessary ability for Language Models (LMs).
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 · 1907
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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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Neural machine translation of rare words with subword units
Rico Sennrich, Barry Haddow, and Alexandra Birch. 2016 · 2016
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Attention is all you need
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Lukasz Kaiser, and Illia Polosukhin. 2017 · 2017
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Parameter-efficient transfer learning for nlp
Neil Houlsby, Andrei Giurgiu, Stanislaw Jastrzebski, Bruna Morrone, Quentin De Laroussilhe, Andrea Gesmundo, Mona Attariyan, and Sylvain Gelly. 2019 · 2019
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Decoupled weight decay regularization
Ilya Loshchilov and Frank Hutter. 2019 · 2019
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Pytorch: An imperative style, high-performance deep learning library
Adam Paszke, Sam Gross, Francisco Massa, Adam Lerer, James Bradbury, Gregory Chanan, Trevor Killeen, Zeming Lin, Natalia Gimelshein, Luca Antiga, et al. 2019 · 2019
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Do NLP models know numbers? probing numeracy in embeddings
Eric Wallace, Yizhong Wang, Sujian Li, Sameer Singh, and Matt Gardner. 2019 · 2019
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A goal-driven tree-structured neural model for math word problems
Zhipeng Xie and Shichao Sun. 2019 · 2019
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Injecting numerical reasoning skills into language models
Mor Geva, Ankit Gupta, and Jonathan Berant. 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
Cited alongside, same era.
Transformers: State-of-the-art natural language processing
Thomas Wolf, Lysandre Debut, Victor Sanh, Julien Chaumond, Clement Delangue, Anthony Moi, Pierric Cistac, Tim Rault, et al. 2020 · 2020
Cited alongside, same era.
Evaluating large language models trained on code
Mark Chen, Jerry Tworek, Heewoo Jun, Qiming Yuan, Henrique Ponde de Oliveira Pinto, Jared Kaplan, Harri Edwards, Yuri Burda, Nicholas Joseph, Greg Brockman, et al. 2021 · 2021
Cited alongside, same era.
Training verifiers to solve math word problems
Karl Cobbe, Vineet Kosaraju, Mohammad Bavarian, Mark Chen, Heewoo Jun, Lukasz Kaiser, Matthias Plappert, Jerry Tworek, Jacob Hilton, Reiichiro Nakano, et al. 2021 · 2021
Cited alongside, same era.
Measuring mathematical problem solving with the math dataset
Pal: Program-aided language models
Luyu Gao, Aman Madaan, Shuyan Zhou, Uri Alon, Pengfei Liu, Yiming Yang, Jamie Callan, and Graham Neubig. 2022 · 2022
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Learning to reason deductively: Math word problem solving as complex relation extraction
Zhanming Jie, Jierui Li, and Wei Lu. 2022 · 2022
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MWP-BERT: Numeracy-augmented pre-training for math word problem solving
Zhenwen Liang, Jipeng Zhang, Lei Wang, Wei Qin, Yunshi Lan, Jie Shao, and Xiangliang Zhang. 2022 · 2022
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Reasoning like program executors
Xinyu Pi, Qian Liu, Bei Chen, Morteza Ziyadi, Zeqi Lin, Yan Gao, Qiang Fu, Jian-Guang Lou, and Weizhu Chen. 2022 · 2022
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Impact of pretraining term frequencies on few-shot reasoning
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Dan Hendrycks, Collin Burns, Saurav Kadavath, Akul Arora, Steven Basart, Eric Tang, Dawn Song, and Jacob Steinhardt. 2021 · 2021
Cited alongside, same era.
Mwptoolkit: An open-source framework for deep learning-based math word problem solvers
Yihuai Lan, Lei Wang, Qiyuan Zhang, Yunshi Lan, Bing Tian Dai, Yan Wang, Dongxiang Zhang, and Ee-Peng Lim. 2021 · 2021
Cited alongside, same era.
Are NLP models really able to solve simple math word problems?
Arkil Patel, Satwik Bhattamishra, and Navin Goyal. 2021 · 2021
Cited alongside, same era.
Math word problem solving with explicit numerical values
Qinzhuo Wu, Qi Zhang, Zhongyu Wei, and Xuanjing Huang. 2021 · 2021
Cited alongside, same era.
Palm: Scaling language modeling with pathways
Aakanksha Chowdhery, Sharan Narang, Jacob Devlin, Maarten Bosma, Gaurav Mishra, Adam Roberts, Paul Barham, Hyung Won Chung, Charles Sutton, Sebastian Gehrmann, et al. 2022 · 2022
Cited alongside, same era.
Yasaman Razeghi, Robert L Logan IV, Matt Gardner, and Sameer Singh. 2022 · 2022
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Differentiable data augmentation for contrastive sentence representation learning
Tianduo Wang and Wei Lu. 2022 · 2022
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Chain of thought prompting elicits reasoning in large language models
Jason Wei, Xuezhi Wang, Dale Schuurmans, Maarten Bosma, Ed Chi, Quoc Le, and Denny Zhou. 2022 · 2022
Later among the works it cites.
Leveraging training data in few-shot prompting for numerical reasoning
Zhanming Jie and Wei Lu. 2023 · 2023
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Self-consistency improves chain of thought reasoning in language models
Xuezhi Wang, Jason Wei, Dale Schuurmans, Quoc Le, Ed Chi, and Denny Zhou. 2023 · 2023
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