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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 natural language.
Roberta: A robustly optimized bert pretraining approach
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Causality for machine learning
Bernhard Schölkopf. 2019 · 1911
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The logic theory machine-a complex information processing system
Allen Newell and Herbert A. Simon. 1956 · 1956
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Programs with common sense
John W. McCarthy. 1959 · 1959
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Causality: Models, Reasoning and Inference
Judea Pearl. 2000 · 2000
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Forward chaining vs. backward chaining
Knut Hinkelmann. 2004 · 2004
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Graphical models for probabilistic and causal reasoning , pages 70–1
J. Pearl. 2004 · 2004
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Causal mediation analysis for interpreting neural NLP: the case of gender bias
Jesse Vig, Sebastian Gehrmann, Yonatan Belinkov, Sharon Qian, Daniel Nevo, Yaron Singer, and Stuart M. Shieber. 2020 · 2004
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The pascal recognising textual entailment challenge
Ido Dagan, Oren Glickman, and Bernardo Magnini. 2006 · 2006
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Towards ai-complete question answering: A set of prerequisite toy tasks
Jason Weston, Antoine Bordes, Sumit Chopra, and Tomás Mikolov. 2016 · 2016
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A unified approach to interpreting model predictions
Scott M. Lundberg and Su-In Lee. 2017 · 2017
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End-to-end differentiable proving
Tim Rocktäschel and Sebastian Riedel. 2017 · 2017
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Axiomatic attribution for deep networks
Mukund Sundararajan, Ankur Taly, and Qiqi Yan. 2017 · 2017
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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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The mythos of model interpretability: In machine learning, the concept of interpretability is both important and slippery
Zachary C. Lipton. 2018 · 2018
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Causal reasoning for algorithmic fairness
Joshua R. Loftus, Chris Russell, Matt J. Kusner, and Ricardo Silva. 2018 · 2018
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Beyond word importance: Contextual decomposition to extract interactions from lstms
W. James Murdoch, Peter J. Liu, and Bin Yu. 2018 · 2018
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NLProlog: Reasoning with weak unification for question answering in natural language
Leon Weber, Pasquale Minervini, Jannes Münchmeyer, Ulf Leser, and Tim Rocktäschel. 2019 · 2019
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Invariance, causality and robustness
Peter Bühlmann. 2020 · 2020
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Transformers as soft reasoners over language
Peter Clark, Oyvind Tafjord, and Kyle Richardson. 2020 · 2020
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Towards faithfully interpretable NLP systems: How should we define and evaluate faithfulness?
Alon Jacovi and Yoav Goldberg. 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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PRover: Proof generation for interpretable reasoning over rules
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Zhilin Yang, Peng Qi, Saizheng Zhang, Yoshua Bengio, William Cohen, Ruslan Salakhutdinov, and Christopher D. Manning. 2018 · 2018
Cited alongside, same era.
BERT: Pre-training of deep bidirectional transformers for language understanding
Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova. 2019 · 2019
Cited alongside, same era.
A survey on semantic parsing
Aishwarya Kamath and Rajarshi Das. 2019 · 2019
Cited alongside, same era.
Reasoning over paragraph effects in situations
Kevin Lin, Oyvind Tafjord, Peter Clark, and Matt Gardner. 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.
QuaRTz: An open-domain dataset of qualitative relationship questions
Oyvind Tafjord, Matt Gardner, Kevin Lin, and Peter Clark. 2019 · 2019
Cited alongside, same era.
Causal inference in natural language processing: Estimation, prediction, interpretation and beyond
Amir Feder, Katherine A. Keith, Emaad Manzoor, Reid Pryzant, Dhanya Sridhar, Zach Wood-Doughty, Jacob Eisenstein, Justin Grimmer, Roi Reichart, Margaret E. Roberts, Brandon M. Stewart, Victor Veitch, and Diyi Yang. 2021a
Cited in the paper.
Swarnadeep Saha, Sayan Ghosh, Shashank Srivastava, and Mohit Bansal. 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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multiPRover: Generating multiple proofs for improved interpretability in rule reasoning
Swarnadeep Saha, Prateek Yadav, and Mohit Bansal. 2021 · 2021
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Discretized integrated gradients for explaining language models
Soumya Sanyal and Xiang Ren. 2021 · 2021
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ProofWriter: Generating implications, proofs, and abductive statements over natural language
Oyvind Tafjord, Bhavana Dalvi, and Peter Clark. 2021 · 2021
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Counterfactual invariance to spurious correlations: Why and how to pass stress tests
Victor Veitch, Alexander D’Amour, Steve Yadlowsky, and Jacob Eisenstein. 2021 · 2021
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