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We introduce a neuro-symbolic natural logic framework based on reinforcement learning with introspective revision.
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Atticus Geiger, Ignacio Cases, Lauri Karttunen, and Christopher Potts. 2019 · 2019
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End-to-end differentiable proving
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Generalization without systematicity: On the compositional skills of sequence-to-sequence recurrent networks
Brenden Lake and Marco Baroni. 2018 · 2018
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The neuro-symbolic concept learner: Interpreting scenes, words, and sentences from natural supervision
Jiayuan Mao, Chuang Gan, Pushmeet Kohli, Joshua B Tenenbaum, and Jiajun Wu. 2018 · 2018
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Leon Weber, Pasquale Minervini, Jannes Münchmeyer, Ulf Leser, and Tim Rocktäschel. 2019 · 2019
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Can neural networks understand monotonicity reasoning?
Hitomi Yanaka, Koji Mineshima, Daisuke Bekki, Kentaro Inui, Satoshi Sekine, Lasha Abzianidze, and Johan Bos. 2019a · 2019
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Eraser: A benchmark to evaluate rationalized nlp models
Jay DeYoung, Sarthak Jain, Nazneen Fatema Rajani, Eric Lehman, Caiming Xiong, Richard Socher, and Byron C Wallace. 2020 · 2020
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Exploring end-to-end differentiable natural logic modeling
Yufei Feng, Zi’ou Zheng, Quan Liu, Michael Greenspan, and Xiaodan Zhu. 2020 · 2020
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Neural natural language inference models partially embed theories of lexical entailment and negation
Atticus Geiger, Kyle Richardson, and Christopher Potts. 2020 · 2020
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Probing linguistic systematicity
Emily Goodwin, Koustuv Sinha, and Timothy J. O’Donnell. 2020 · 2020
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spaCy: Industrial-strength Natural Language Processing in Python
Matthew Honnibal, Ines Montani, Sofie Van Landeghem, and Adriane Boyd. 2020 · 2020
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MonaLog: a lightweight system for natural language inference based on monotonicity
Hai Hu, Qi Chen, Kyle Richardson, Atreyee Mukherjee, Lawrence S Moss, and Sandra Kuebler. 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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Hy-nli: a hybrid system for natural language inference
Aikaterini-Lida Kalouli, Richard Crouch, and Valeria de Paiva. 2020 · 2020
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Closed loop neural-symbolic learning via integrating neural perception, grammar parsing, and symbolic reasoning
Qing Li, Siyuan Huang, Yining Hong, Yixin Chen, Ying Nian Wu, and Song-Chun Zhu. 2020 · 2020
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Probing natural language inference models through semantic fragments
Kyle Richardson, Hai Hu, Lawrence S Moss, and Ashish Sabharwal. 2020 · 2020
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Do neural models learn systematicity of monotonicity inference in natural language?
Hitomi Yanaka, Koji Mineshima, Daisuke Bekki, and Kentaro Inui. 2020 · 2020
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Neurallog: Natural language inference with joint neural and logical reasoning
Zeming Chen, Qiyue Gao, and Lawrence S Moss. 2021 · 2021
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Weakly supervised explainable phrasal reasoning with neural fuzzy logic
Zijun Wu, Atharva Naik, Zi Xuan Zhang, and Lili Mou. 2021 · 2021
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