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Recent success of pre-trained language models (LMs) has spurred widespread interest in the language capabilities that they possess.
Assessing bert’s syntactic abilities
Yoav Goldberg. 2019 · 1901
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Learning and evaluating general linguistic intelligence
D. Yogatama, C. de M. d’Autume, J. Connor, T. Kocisky, M. Chrzanowski, L. Kong, A. Lazaridou, W. Ling, L. Yu, C. Dyer, et al. 2019 · 1901
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Visualizing and measuring the geometry of bert
Andy Coenen, Emily Reif, Ann Yuan, Been Kim, Adam Pearce, Fernanda Viégas, and Martin Wattenberg. 2019 · 1906
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What bert is not: Lessons from a new suite of psycholinguistic diagnostics for language models
Allyson Ettinger. 2019 · 1907
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Roberta: A robustly optimized bert pretraining approach
Yinhan Liu, Myle Ott, Naman Goyal, Jingfei Du, Mandar Joshi, Danqi Chen, Omer Levy, Mike Lewis, Luke Zettlemoyer, and Veselin Stoyanov. 2019 · 1907
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Question answering is a format; when is it useful?
Matt Gardner, Jonathan Berant, Hannaneh Hajishirzi, Alon Talmor, and Sewon Min. 2019b · 1909
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How can we know what language models know?
Zhengbao Jiang, Frank F. Xu, Jun Araki, and Graham Neubig. 2019 · 1911
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Adverbs of quantification
David Lewis. 1975 · 1975
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Generalized quantifiers and natural language
Jon Barwise and Robin Cooper. 1981 · 1981
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WordNet: An Electronic Lexical Database
C. Fellbaum. 1998 · 1998
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Donald Davidson’s truth-theoretic semantics
Ernest Lepore and Kirk Ludwig. 2007 · 2007
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Reporting bias and knowledge acquisition
Jonathan Gordon and Benjamin Van Durme. 2013 · 2013
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GloVe: Global vectors for word representation
J. Pennington, R. Socher, and C. D. Manning. 2014 · 2014
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Wikidata: A free collaborative knowledgebase
D. Vrandečić and M. Krőtzsch. 2014 · 2014
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Semi-supervised sequence learning
Andrew M Dai and Quoc V Le. 2015 · 2015
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Building a shared world: Mapping distributional to model-theoretic semantic spaces
Aurélie Herbelot and Eva Maria Vecchi. 2015 · 2015
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Fine-grained analysis of sentence embeddings using auxiliary prediction tasks
Yossi Adi, Einat Kermany, Yonatan Belinkov, Ofer Lavi, and Yoav Goldberg. 2016 · 2016
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Are elephants bigger than butterflies? reasoning about sizes of objects
Hessam Bagherinezhad, Hannaneh Hajishirzi, Yejin Choi, and Ali Farhadi. 2016 · 2016
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Probing for semantic evidence of composition by means of simple classification tasks
Allyson Ettinger, Ahmed Elgohary, and Philip Resnik. 2016 · 2016
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Neural machine translation of rare words with subword units
Rico Sennrich, Barry Haddow, and Alexandra Birch. 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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Verb physics: Relative physical knowledge of actions and objects
Maxwell Forbes and Yejin Choi. 2017 · 2017
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Conceptnet 5.5: An open multilingual graph of general knowledge
Robyn Speer, Joshua Chin, and Catherine Havasi. 2017 · 2017
How large are lions? inducing distributions over quantitative attributes
Yanai Elazar, Abhijit Mahabal, Deepak Ramachandran, Tania Bedrax-Weiss, and Dan Roth. 2019 · 2019
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Designing and interpreting probes with control tasks
John Hewitt and Percy Liang. 2019 · 2019
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A structural probe for finding syntax in word representations
John Hewitt and Christopher D. Manning. 2019 · 2019
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Knowledge of animal appearance among sighted and blind adults
Judy S Kim, Giulia V Elli, and Marina Bedny. 2019 · 2019
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Open sesame: Getting inside bert’s linguistic knowledge
Yongjie Lin, Yi Chern Tan, and Robert Frank. 2019 · 2019
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Language models as knowledge bases?
Fabio Petroni, Tim Rocktäschel, Sebastian Riedel, Patrick Lewis, Anton Bakhtin, Yuxiang Wu, and Alexander Miller. 2019 · 2019
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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
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Premise selection for theorem proving by deep graph embedding
Mingzhe Wang, Yihe Tang, Jian Wang, and Jia Deng. 2017 · 2017
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The description length of deep learning models
Léonard Blier and Yann Ollivier. 2018 · 2018
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Can a suit of armor conduct electricity? a new dataset for open book question answering
Todor Mihaylov, Peter Clark, Tushar Khot, and Ashish Sabharwal. 2018 · 2018
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Dissecting contextual word embeddings: Architecture and representation
Matthew Peters, Mark Neumann, Luke Zettlemoyer, and Wen-tau Yih. 2018b · 2018
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The web as knowledge-base for answering complex questions
A. Talmor and J. Berant. 2018 · 2018
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Is the red square big? malevic: Modeling adjectives leveraging visual contexts
Sandro Pezzelle and Raquel Fernández. 2019 · 2019
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Language models are unsupervised multitask learners
Alec Radford, Jeffrey Wu, Rewon Child, David Luan, Dario Amodei, and Ilya Sutskever. 2019 · 2019
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Diversify your datasets: Analyzing generalization via controlled variance in adversarial datasets
Ohad Rozen, Vered Shwartz, Roee Aharoni, and Ido Dagan. 2019 · 2019
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Still a pain in the neck: Evaluating text representations on lexical composition
Vered Shwartz and Ido Dagan. 2019 · 2019
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Commonsenseqa: A question answering challenge targeting commonsense knowledge
A. Talmor, J. Herzig, N. Lourie, and J. Berant. 2019 · 2019
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Do nlp models know numbers? probing numeracy in embeddings
Eric Wallace, Yizhong Wang, Sujian Li, Sameer Singh, and Matt Gardner. 2019 · 2019
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Investigating bert’s knowledge of language: Five analysis methods with npis
Alex Warstadt, Yu Cao, Ioana Grosu, Wei Peng, Hagen Blix, Yining Nie, Anna Alsop, Shikha Bordia, Haokun Liu, Alicia Parrish, et al. 2019 · 2019
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Xlnet: Generalized autoregressive pretraining for language understanding
Zhilin Yang, Zihang Dai, Yiming Yang, Jaime Carbonell, Russ R Salakhutdinov, and Quoc V Le. 2019 · 2019
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Negated and misprimed probes for pretrained language models: Birds can talk, but cannot fly
Nora Kassner and Hinrich Schütze. 2020 · 2020
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Adversarial NLI: A new benchmark for natural language understanding
Yixin Nie, Adina Williams, Emily Dinan, Mohit Bansal, Jason Weston, and Douwe Kiela. 2020 · 2020
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