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Neural network models have been very successful at achieving high accuracy on natural language inference (NLI) tasks.
Hellaswag: Can a machine really finish your sentence?
Rowan Zellers, Ari Holtzman, Yonatan Bisk, Ali Farhadi, and Yejin Choi. 2019 · 1905
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Wordnet: a lexical database for english
George A Miller. 1995 · 1995
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Robust textual inference via graph matching
Aria D Haghighi, Andrew Y Ng, and Christopher D Manning. 2005 · 2005
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Robust textual inference using diverse knowledge sources
Rajat Raina, Aria Haghighi, Christopher Cox, Jenny Finkel, Jeff Michels, Kristina Toutanova, Bill MacCartney, Marie-Catherine de Marneffe, Christopher D Manning, and Andrew Y Ng. 2005 · 2005
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Learning structured embeddings of knowledge bases
Antoine Bordes, Jason Weston, Ronan Collobert, and Yoshua Bengio. 2011 · 2011
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Recognizing textual entailment: Models and applications
Ido Dagan, Dan Roth, Mark Sammons, and Fabio Massimo Zanzotto. 2013 · 2013
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Retrofitting word vectors to semantic lexicons
Manaal Faruqui, Jesse Dodge, Sujay K Jauhar, Chris Dyer, Eduard Hovy, and Noah A Smith. 2014 · 2014
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Adam: A method for stochastic optimization
Diederik P Kingma and Jimmy Ba. 2014 · 2014
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Glove: Global vectors for word representation
Jeffrey Pennington, Richard Socher, and Christopher Manning. 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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Semi-supervised sequence learning
Andrew M Dai and Quoc V Le. 2015 · 2015
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Reasoning about entailment with neural attention
Tim Rocktäschel, Edward Grefenstette, Karl Moritz Hermann, Tomáš Kočiskỳ, and Phil Blunsom. 2015 · 2015
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A fast unified model for parsing and sentence understanding
Samuel R Bowman, Jon Gauthier, Abhinav Rastogi, Raghav Gupta, Christopher D Manning, and Christopher Potts. 2016 · 2016
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Enhanced lstm for natural language inference
Qian Chen, Xiaodan Zhu, Zhenhua Ling, Si Wei, Hui Jiang, and Diana Inkpen. 2016 · 2016
Cited alongside, same era.
Gaussian error linear units (gelus)
Dan Hendrycks and Kevin Gimpel. 2016 · 2016
Cited alongside, same era.
Harnessing deep neural networks with logic rules
Zhiting Hu, Xuezhe Ma, Zhengzhong Liu, Eduard Hovy, and Eric Xing. 2016 · 2016
Cited alongside, same era.
Counter-fitting word vectors to linguistic constraints
Nikola Mrkšić, Diarmuid O Séaghdha, Blaise Thomson, Milica Gašić, Lina Rojas-Barahona, Pei-Hao Su, David Vandyke, Tsung-Hsien Wen, and Steve Young. 2016 · 2016
Cited alongside, same era.
A decomposable attention model for natural language inference
Annotation artifacts in natural language inference data
Suchin Gururangan, Swabha Swayamdipta, Omer Levy, Roy Schwartz, Samuel R Bowman, and Noah A Smith. 2018 · 2018
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Universal language model fine-tuning for text classification
Jeremy Howard and Sebastian Ruder. 2018 · 2018
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Adventure: Adversarial training for textual entailment with knowledge-guided examples
Dongyeop Kang, Tushar Khot, Ashish Sabharwal, and Eduard Hovy. 2018 · 2018
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SciTail: A textual entailment dataset from science question answering
Tushar Khot, Ashish Sabharwal, and Peter Clark. 2018 · 2018
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Ankur P Parikh, Oscar Täckström, Dipanjan Das, and Jakob Uszkoreit. 2016 · 2016
Cited alongside, same era.
Neural natural language inference models enhanced with external knowledge
Qian Chen, Xiaodan Zhu, Zhen-Hua Ling, Diana Inkpen, and Si Wei. 2017 · 2017
Cited alongside, same era.
Shortcut-stacked sentence encoders for multi-domain inference
Yixin Nie and Mohit Bansal. 2017 · 2017
Cited alongside, same era.
Semi-supervised sequence tagging with bidirectional language models
Matthew E Peters, Waleed Ammar, Chandra Bhagavatula, and Russell Power. 2017 · 2017
Cited alongside, same era.
Yi Tay, Luu Anh Tuan, and Siu Cheung Hui. 2017 · 2017
Cited alongside, same era.
Attention is all you need
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Łukasz Kaiser, and Illia Polosukhin. 2017 · 2017
Cited alongside, same era.
Bert: Pre-training of deep bidirectional transformers for language understanding
Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova. 2018 · 2018
Cited alongside, same era.
Breaking nli systems with sentences that require simple lexical inferences
Max Glockner, Vered Shwartz, and Yoav Goldberg. 2018 · 2018
Cited alongside, same era.
Matthew E Peters, Mark Neumann, Mohit Iyyer, Matt Gardner, Christopher Clark, Kenton Lee, and Luke Zettlemoyer. 2018 · 2018
Later among the works it cites.
Improving language understanding by generative pre-training
Alec Radford, Karthik Narasimhan, Tim Salimans, and Ilya Sutskever. 2018 · 2018
Later among the works it cites.
Reinforced self-attention network: a hybrid of hard and soft attention for sequence modeling
Tao Shen, Tianyi Zhou, Guodong Long, Jing Jiang, Sen Wang, and Chengqi Zhang. 2018 · 2018
Later among the works it cites.
Recognizing and justifying text entailment through distributional navigation on definition graphs
Vivian S Silva, Siegfried Handschuh, and André Freitas. 2018 · 2018
Later among the works it cites.
GLUE: A multi-task benchmark and analysis platform for natural language understanding
Alex Wang, Amanpreet Singh, Julian Michael, Felix Hill, Omer Levy, and Samuel R. Bowman. 2018 · 2018
Later among the works it cites.
A broad-coverage challenge corpus for sentence understanding through inference
Adina Williams, Nikita Nangia, and Samuel Bowman. 2018 · 2018
Later among the works it cites.
Swag: A large-scale adversarial dataset for grounded commonsense inference
Rowan Zellers, Yonatan Bisk, Roy Schwartz, and Yejin Choi. 2018 · 2018
Later among the works it cites.
Improving question answering by commonsense-based pre-training
Wanjun Zhong, Duyu Tang, Nan Duan, Ming Zhou, Jiahai Wang, and Jian Yin. 2018 · 2018
Later among the works it cites.