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Unsupervised pretraining models have been shown to facilitate a wide range of downstream NLP applications.
ERNIE: Enhanced language representation with informative entities
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A simple BERT-based approach for lexical simplification
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ERNIE 2.0: A continual pre-training framework for language understanding
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BabelNet: The automatic construction, evaluation and application of a wide-coverage multilingual semantic network
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Distributed representations of words and phrases and their compositionality
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Recursive deep models for semantic compositionality over a sentiment treebank
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Learning a lexical simplifier using Wikipedia
Colby Horn, Cathryn Manduca, and David Kauchak. 2014 · 2014
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Improving lexical embeddings with semantic knowledge
Mo Yu and Mark Dredze. 2014 · 2014
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Word semantic representations using Bayesian probabilistic tensor factorization
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Retrofitting word vectors to semantic lexicons
Manaal Faruqui, Jesse Dodge, Sujay Kumar Jauhar, Chris Dyer, Eduard Hovy, and Noah A. Smith. 2015 · 2015
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Simplifying lexical simplification: Do we need simplified corpora?
Goran Glavaš and Sanja Štajner. 2015 · 2015
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Felix Hill, Roi Reichart, and Anna Korhonen. 2015 · 2015
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Learning semantic word embeddings based on ordinal knowledge constraints
Quan Liu, Hui Jiang, Si Wei, Zhen-Hua Ling, and Yu Hu. 2015 · 2015
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Symmetric pattern based word embeddings for improved word similarity prediction
Roy Schwartz, Roi Reichart, and Ari Rappoport. 2015 · 2015
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From paraphrase database to compositional paraphrase model and back
John Wieting, Mohit Bansal, Kevin Gimpel, and Karen Livescu. 2015 · 2015
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Diverse Context for Learning Word Representations
Manaal Faruqui. 2016 · 2016
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Intent detection using semantically enriched word embeddings
Joo-Kyung Kim, Gokhan Tur, Asli Celikyilmaz, Bin Cao, and Ye-Yi Wang. 2016 · 2016
Extrofitting: Enriching word representation and its vector space with semantic lexicons
Hwiyeol Jo and Stanley Jungkyu Choi. 2018 · 2018
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Deep contextualized word representations
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Adversarial propagation and zero-shot cross-lingual transfer of word vector specialization
Edoardo Maria Ponti, Ivan Vulić, Goran Glavaš, Nikola Mrkšić, and Anna Korhonen. 2018 · 2018
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Improving language understanding by generative pre-training
Alec Radford, Karthik Narasimhan, Tim Salimans, and Ilya Sutskever. 2018 · 2018
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Towards universal dialogue state tracking
Liliang Ren, Kaige Xie, Lu Chen, and Kai Yu. 2018 · 2018
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Counter-fitting word vectors to linguistic constraints
Nikola Mrkšić, Diarmuid Ó Séaghdha, Blaise Thomson, Milica Gašić, Lina Maria Rojas-Barahona, Pei-Hao Su, David Vandyke, Tsung-Hsien Wen, and Steve Young. 2016 · 2016
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Encoding prior knowledge with eigenword embeddings
Dominique Osborne, Shashi Narayan, and Shay Cohen. 2016 · 2016
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Benchmarking lexical simplification systems
Gustavo Paetzold and Lucia Specia. 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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Google’s neural machine translation system: Bridging the gap between human and machine translation
Yonghui Wu, Mike Schuster, Zhifeng Chen, Quoc V Le, Mohammad Norouzi, Wolfgang Macherey, Maxim Krikun, Yuan Cao, Qin Gao, Klaus Macherey, et al. 2016 · 2016
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Enriching word vectors with subword information
Piotr Bojanowski, Edouard Grave, Armand Joulin, and Tomas Mikolov. 2017 · 2017
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Injecting lexical contrast into word vectors by guiding vector space specialisation
Ivan Vulić. 2018 · 2018
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Post-specialisation: Retrofitting vectors of words unseen in lexical resources
Ivan Vulić, Goran Glavaš, Nikola Mrkšić, and Anna Korhonen. 2018 · 2018
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Specialising word vectors for lexical entailment
Ivan Vulić and Nikola Mrkšić. 2018 · 2018
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GLUE: A multi-task benchmark and analysis platform for natural language understanding
Alex Wang, Amanpreet Singh, Julian Michael, Felix Hill, Omer Levy, and Samuel Bowman. 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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BERT: Pre-training of deep bidirectional transformers for language understanding
Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova. 2019 · 2019
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Specializing distributional vectors of all words for lexical entailment
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Knowledge enhanced contextual word representations
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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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Cross-lingual semantic specialization via lexical relation induction
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Language models are unsupervised multitask learners
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Neural network acceptability judgments
Alex Warstadt, Amanpreet Singh, and Samuel R Bowman. 2019 · 2019
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Specializing word embeddings for similarity or relatedness
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