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The task of natural language inference (NLI) is to identify the relation between the given premise and hypothesis.
Multi-task deep neural networks for natural language understanding
Xiaodong Liu, Pengcheng He, Weizhu Chen, and Jianfeng Gao. 2019b · 1901
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Learning and evaluating general linguistic intelligence
Dani Yogatama, Cyprien de Masson d’Autume, Jerome Connor, Tomas Kocisky, Mike Chrzanowski, Lingpeng Kong, Angeliki Lazaridou, Wang Ling, Lei Yu, Chris Dyer, et al. 2019 · 1901
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Right for the wrong reasons: Diagnosing syntactic heuristics in natural language inference
R Thomas McCoy, Ellie Pavlick, and Tal Linzen. 2019 · 1902
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Inoculation by fine-tuning: A method for analyzing challenge datasets
Nelson F Liu, Roy Schwartz, and Noah A Smith. 2019a · 1904
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Entailment, intensionality and text understanding
Cleo Condoravdi, Dick Crouch, Valeria de Paiva, Reinhard Stolle, and Daniel G. Bobrow. 2003 · 2003
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The PASCAL recognising textual entailment challenge
Ido Dagan, Oren Glickman, and Bernardo Magnini. 2006 · 2006
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A SICK cure for the evaluation of compositional distributional semantic models
M. Marelli, S. Menini, M. Baroni, L. Bentivogli, R. Bernardi, and R. Zamparelli. 2014 · 2014
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A large annotated corpus for learning natural language inference
Samuel R. Bowman, Gabor Angeli, Christopher Potts, and Christopher D. Manning. 2015 · 2015
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Question-answer driven semantic role labeling: Using natural language to annotate natural language
Luheng He, Mike Lewis, and Luke Zettlemoyer. 2015 · 2015
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Pointer networks
Oriol Vinyals, Meire Fortunato, and Navdeep Jaitly. 2015 · 2015
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A decomposable attention model for natural language inference
Ankur Parikh, Oscar Täckström, Dipanjan Das, and Jakob Uszkoreit. 2016 · 2016
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Squad: 100,000+ questions for machine comprehension of text
Pranav Rajpurkar, Jian Zhang, Konstantin Lopyrev, and Percy Liang. 2016 · 2016
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Enhanced lstm for natural language inference
Qian Chen, Xiaodan Zhu, Zhen-Hua Ling, Si Wei, Hui Jiang, and Diana Inkpen. 2017 · 2017
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Bidirectional attention flow for machine comprehension
Minjoon Seo, Aniruddha Kembhavi, Ali Farhadi, and Hannaneh Hajishirzi. 2017 · 2017
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Neural natural language inference models enhanced with external knowledge
Qian Chen, Xiaodan Zhu, Zhen-Hua Ling, Diana Inkpen, and Si Wei. 2018 · 2018
The natural language decathlon: Multitask learning as question answering
Bryan McCann, Nitish Shirish Keskar, Caiming Xiong, and Richard Socher. 2018 · 2018
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Non-entailed subsequences as a challenge for natural language inference
R Thomas McCoy and Tal Linzen. 2018 · 2018
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Stress test evaluation for natural language inference
Aakanksha Naik, Abhilasha Ravichander, Norman Sadeh, Carolyn Rose, and Graham Neubig. 2018 · 2018
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Deep contextualized word representations
Matthew Peters, Mark Neumann, Mohit Iyyer, Matt Gardner, Christopher Clark, Kenton Lee, and Luke Zettlemoyer. 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
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Breaking nli systems with sentences that require simple lexical inferences
Max Glockner, Vered Shwartz, and Yoav Goldberg. 2018 · 2018
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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
Cited alongside, same era.
pair2vec: Compositional word-pair embeddings for cross-sentence inference
Mandar Joshi, Eunsol Choi, Omer Levy, Daniel S Weld, and Luke Zettlemoyer. 2018 · 2018
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A broad-coverage challenge corpus for sentence understanding through inference
Adina Williams, Nikita Nangia, and Samuel Bowman. 2018 · 2018
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Analyzing compositionality-sensitivity of nli models
Yixin Nie, Yicheng Wang, and Mohit Bansal. 2019 · 2019
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Coala: A neural coverage-based approach for long answer selection with small data
Andreas Rücklé, Nafise Sadat Moosavi, and Iryna Gurevych. 2019 · 2019
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