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We introduce Rosita, a method to produce multilingual contextual word representations by training a single language model on text from multiple languages.
Cross-lingual language model pretraining
Guillaume Lample and Alexis Conneau. 2019 · 1901
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Adaptive subgradient methods for online learning and stochastic optimization
John C. Duchi, Elad Hazan, and Yoram Singer. 2011 · 2011
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ADADELTA: an adaptive learning rate method
Matthew D Zeiler. 2012 · 2012
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One billion word benchmark for measuring progress in statistical language modeling
Ciprian Chelba, Tomas Mikolov, Mike Schuster, Qi Ge, Thorsten Brants, Phillipp Koehn, and Tony Robinson. 2013 · 2013
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Towards robust linguistic analysis using ontonotes
Sameer Pradhan, Alessandro Moschitti, Nianwen Xue, Hwee Tou Ng, Anders Björkelund, Olga Uryupina, Yuchen Zhang, and Zhi Zhong. 2013 · 2013
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Improving vector space word representations using multilingual correlation
Manaal Faruqui and Chris Dyer. 2014 · 2014
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The Stanford CoreNLP natural language processing toolkit
Christopher D. Manning, Mihai Surdeanu, John Bauer, Jenny Finkel, Steven J. Bethard, and David McClosky. 2014 · 2014
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ADAM: A method for stochastic optimization
Diederik P. Kingma and Jimmy Lei Ba. 2015 · 2015
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Towards a Universal Analyzer of Natural Languages
Waleed Ammar. 2016 · 2016
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Many languages, one parser
Waleed Ammar, George Mulcaire, Miguel Ballesteros, Chris Dyer, and Noah A. Smith. 2016 · 2016
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Multi-language neural network language models
Anton Ragni, Edgar Dakin, Xie Chen, Mark J. F. Gales, and Kate Knill. 2016 · 2016
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UDPipe: Trainable pipeline for processing conll-u files performing tokenization, morphological analysis, pos tagging and parsing
Milan Straka, Jan Hajic, and Jana Straková. 2016 · 2016
Cited alongside, same era.
Polyglot neural language models: A case study in cross-lingual phonetic representation learning
Yulia Tsvetkov, Sunayana Sitaram, Manaal Faruqui, Guillaume Lample, Patrick Littell, David Mortensen, Alan W Black, Lori Levin, and Chris Dyer. 2016 · 2016
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Cross-lingual models of word embeddings: An empirical comparison
Shyam Upadhyay, Manaal Faruqui, Chris Dyer, and Dan Roth. 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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Deep biaffine attention for neural dependency parsing
Timothy Dozat and Christopher Manning. 2017 · 2017
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Word translation without parallel data
Alexis Conneau, Guillaume Lample, Marc’Aurelio Ranzato, Ludovic Denoyer, and Hervé Jégou. 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. 2018 · 2018
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AllenNLP: A deep semantic natural language processing platform
Matt Gardner, Joel Grus, Mark Neumann, Oyvind Tafjord, Pradeep Dasigi, Nelson Liu, Matthew Peters, Michael Schmitz, and Luke Zettlemoyer. 2018 · 2018
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Parameter sharing between dependency parsers for related languages
Miryam de Lhoneux, Johannes Bjerva, Isabelle Augenstein, and Anders Søgaard. 2018 · 2018
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Polyglot semantic role labeling
Phoebe Mulcaire, Swabha Swayamdipta, and Noah A Smith. 2018 · 2018
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CoNLL 2017 shared task - automatically annotated raw texts and word embeddings
Filip Ginter, Jan Hajič, Juhani Luotolahti, Milan Straka, and Daniel Zeman. 2017 · 2017
Cited alongside, same era.
Deep semantic role labeling: What works and what’s next
Luheng He, Kenton Lee, Mike Lewis, and Luke Zettlemoyer. 2017 · 2017
Cited alongside, same era.
Semi-supervised sequence tagging with bidirectional language models
Matthew Peters, Waleed Ammar, Chandra Bhagavatula, and Russell Power. 2017 · 2017
Cited alongside, same era.
A survey of cross-lingual word embedding models
Sebastian Ruder, Ivan Vulić, and Anders Søgaard. 2017 · 2017
Cited alongside, same era.
Towards better UD parsing: Deep contextualized word embeddings, ensemble, and treebank concatenation
Wanxiang Che, Yijia Liu, Yuxuan Wang, Bo Zheng, and Ting Liu. 2018 · 2018
Cited alongside, same era.
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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Universal dependency parsing from scratch
Peng Qi, Timothy Dozat, Yuhao Zhang, and Christopher D. Manning. 2018 · 2018
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Deep active learning for named entity recognition
Yanyao Shen, Hyokun Yun, Zachary Lipton, Yakov Kronrod, and Animashree Anandkumar. 2018 · 2018
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Neural cross-lingual named entity recognition with minimal resources
Jiateng Xie, Zhilin Yang, Graham Neubig, Noah A. Smith, and Jaime Carbonell. 2018 · 2018
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CoNLL 2018 shared task: Multilingual parsing from raw text to universal dependencies
Daniel Zeman, Jan Hajič, Martin Popel, Martin Potthast, Milan Straka, Filip Ginter, Joakim Nivre, and Slav Petrov. 2018 · 2018
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