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Transformers have been shown to be able to perform deductive reasoning on a logical rulebase containing rules and statements written in English natural language.
Roberta: A robustly optimized bert pretraining approach
Yinhan Liu, Myle Ott, Naman Goyal, and Jingfei Du an. 2019 · 1907
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Programs with common sense
John W. McCarthy. 1959 · 1959
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The pascal recognising textual entailment challenge
Ido Dagan, Oren Glickman, and Bernardo Magnini. 2006 · 2006
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Scikit-learn: Machine learning in Python
F. Pedregosa, G. Varoquaux, A. Gramfort, V. Michel, B. Thirion, O. Grisel, M. Blondel, P. Prettenhofer, R. Weiss, V. Dubourg, J. Vanderplas, A. Passos, D. Cournapeau, M. Brucher, M. Perrot, and E. Duchesnay. 2011 · 2011
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Race: Large-scale reading comprehension dataset from examinations
Guokun Lai, Qizhe Xie, Hanxiao Liu, Yiming Yang, and Eduard Hovy. 2017 · 2017
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End-to-end differentiable proving
Tim Rocktäschel and S. Riedel. 2017 · 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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HotpotQA: A dataset for diverse, explainable multi-hop question answering
Zhilin Yang, Peng Qi, Saizheng Zhang, Yoshua Bengio, William Cohen, Ruslan Salakhutdinov, and Christopher D. Manning. 2018a · 2018
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HotpotQA: A dataset for diverse, explainable multi-hop question answering
Zhilin Yang, Peng Qi, Saizheng Zhang, Yoshua Bengio, William Cohen, Ruslan Salakhutdinov, and Christopher D. Manning. 2018b · 2018
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Understanding dataset design choices for multi-hop reasoning
Jifan Chen and Greg Durrett. 2019 · 2019
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Decoupled weight decay regularization
Ilya Loshchilov and Frank Hutter. 2019 · 2019
Cited alongside, same era.
Deepproblog: Neural probabilistic logic programming
Robin Manhaeve, Sebastijan Dumancic, A. Kimmig, T. Demeester, and L. D. Raedt. 2019 · 2019
Cited alongside, same era.
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.
CLUTRR: A diagnostic benchmark for inductive reasoning from text
Koustuv Sinha, Shagun Sodhani, Jin Dong, Joelle Pineau, and William L. Hamilton. 2019 · 2019
Cited alongside, same era.
Language models are few-shot learners
Tom Brown, Benjamin Mann, Nick Ryder, Melanie Subbiah, Jared D Kaplan, Prafulla Dhariwal, Arvind Neelakantan, Pranav Shyam, Girish Sastry, Amanda Askell, Sandhini Agarwal, Ariel Herbert-Voss, Gretchen Krueger, Tom Henighan, Rewon Child, Aditya Ramesh, Daniel Ziegler, Jeffrey Wu, Clemens Winter, Chris Hesse, Mark Chen, Eric Sigler, Mateusz Litwin, Scott Gray, Benjamin Chess, Jack Clark, Christopher Berner, Sam McCandlish, Alec Radford, Ilya Sutskever, and Dario Amodei. 2020 · 2020
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Exploring the limits of transfer learning with a unified text-to-text transformer
Colin Raffel, Noam Shazeer, Adam Roberts, Katherine Lee, Sharan Narang, Michael Matena, Yanqi Zhou, Wei Li, and Peter J. Liu. 2020 · 2020
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Transformers: State-of-the-art natural language processing
Thomas Wolf, Lysandre Debut, Victor Sanh, Julien Chaumond, Clement Delangue, Anthony Moi, Pierric Cistac, Tim Rault, Remi Louf, Morgan Funtowicz, Joe Davison, Sam Shleifer, Patrick von Platen, Clara Ma, Yacine Jernite, Julien Plu, Canwen Xu, Teven Le Scao, Sylvain Gugger, Mariama Drame, Quentin Lhoest, and Alexander Rush. 2020 · 2020
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Reclor: A reading comprehension dataset requiring logical reasoning
Weihao Yu, Zihang Jiang, Yanfei Dong, and Jiashi Feng. 2020 · 2020
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Logiqa: A challenge dataset for machine reading comprehension with logical reasoning
Jian Liu, Leyang Cui, Hanmeng Liu, Dandan Huang, Yile Wang, and Yue Zhang. 2021 · 2021
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Multitask prompted training enables zero-shot task generalization
Victor Sanh, Albert Webson, Colin Raffel, Stephen H Bach, Lintang Sutawika, Zaid Alyafeai, Antoine Chaffin, Arnaud Stiegler, Teven Le Scao, Arun Raja, et al. 2021 · 2021
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Transformers as soft reasoners over language
Peter Clark, Oyvind Tafjord, and Kyle Richardson. 2020 · 2020
Cited alongside, same era.
MuTual: A dataset for multi-turn dialogue reasoning
Leyang Cui, Yu Wu, Shujie Liu, Yue Zhang, and Ming Zhou. 2020 · 2020
Cited alongside, same era.
Evaluating models’ local decision boundaries via contrast sets
Matt Gardner, Yoav Artzi, Victoria Basmov, Jonathan Berant, Ben Bogin, Sihao Chen, Pradeep Dasigi, Dheeru Dua, Yanai Elazar, Ananth Gottumukkala, Nitish Gupta, Hannaneh 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
Cited alongside, same era.
Measuring systematic generalization in neural proof generation with transformers
Nicolas Gontier, Koustuv Sinha, Siva Reddy, and C. Pal. 2020 · 2020
Cited alongside, same era.
Later among the works it cites.
ProofWriter: Generating implications, proofs, and abductive statements over natural language
Oyvind Tafjord, Bhavana Dalvi, and Peter Clark. 2021 · 2021
Later among the works it cites.
RICA: Evaluating robust inference capabilities based on commonsense axioms
Pei Zhou, Rahul Khanna, Seyeon Lee, Bill Yuchen Lin, Daniel Ho, Jay Pujara, and Xiang Ren. 2021 · 2021
Later among the works it cites.
FaiRR: Faithful and robust deductive reasoning over natural language
Soumya Sanyal, Harman Singh, and Xiang Ren. 2022 · 2022
Closest in time.
On the paradox of learning to reason from data
Honghua Zhang, Liunian Harold Li, Tao Meng, Kai-Wei Chang, and Guy Van den Broeck. 2022 · 2022
Closest in time.