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We introduce a novel method for multilingual transfer that utilizes deep contextual embeddings, pretrained in an unsupervised fashion.
Context-aware crosslingual mapping
Hanan Aldarmaki and Mona Diab. 2019 · 1903
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Semi-supervised sequence modeling with cross-view training
Kevin Clark, Minh-Thang Luong, Christopher D. Manning, and Quoc Le. 2018 · 1925
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Dropout: A simple way to prevent neural networks from overfitting
Nitish Srivastava, Geoffrey Hinton, Alex Krizhevsky, Ilya Sutskever, and Ruslan Salakhutdinov. 2014 · 1958
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Adversarial training for unsupervised bilingual lexicon induction
Meng Zhang, Yang Liu, Huanbo Luan, and Maosong Sun. 2017 · 1970
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Multi-source transfer of delexicalized dependency parsers
Ryan McDonald, Slav Petrov, and Keith Hall. 2011 · 2011
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Selective sharing for multilingual dependency parsing
Tahira Naseem, Regina Barzilay, and Amir Globerson. 2012 · 2012
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A universal part-of-speech tagset
Slav Petrov, Dipanjan Das, and Ryan McDonald. 2012 · 2012
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Parallel data, tools and interfaces in OPUS
Jörg Tiedemann. 2012 · 2012
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A simple, fast, and effective reparameterization of IBM model 2
Chris Dyer, Victor Chahuneau, and Noah A. Smith. 2013 · 2013
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Exploiting similarities among languages for machine translation
Tomas Mikolov, Quoc V. Le, and Ilya Sutskever. 2013 · 2013
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Improving zero-shot learning by mitigating the hubness problem
Georgiana Dinu and Marco Baroni. 2014 · 2014
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Distributed word representation learning for cross-lingual dependency parsing
Min Xiao and Yuhong Guo. 2014 · 2014
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Cross-lingual transfer for unsupervised dependency parsing without parallel data
Long Duong, Trevor Cohn, Steven Bird, and Paul Cook. 2015 · 2015
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Cross-lingual dependency parsing based on distributed representations
Jiang Guo, Wanxiang Che, David Yarowsky, Haifeng Wang, and Ting Liu. 2015 · 2015
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Hubness and pollution: Delving into cross-space mapping for zero-shot learning
Angeliki Lazaridou, Georgiana Dinu, and Marco Baroni. 2015 · 2015
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Cross-lingual dependency parsing with universal dependencies and predicted POS labels
Jörg Tiedemann. 2015 · 2015
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Annotation projection-based representation learning for cross-lingual dependency parsing
Min Xiao and Yuhong Guo. 2015 · 2015
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Normalized word embedding and orthogonal transform for bilingual word translation
Chao Xing, Dong Wang, Chao Liu, and Yiye Lin. 2015 · 2015
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Hierarchical low-rank tensors for multilingual transfer parsing
Yuan Zhang and Regina Barzilay. 2015 · 2015
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Many languages, one parser
Waleed Ammar, George Mulcaire, Miguel Ballesteros, Chris Dyer, and Noah Smith. 2016 · 2016
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A representation learning framework for multi-source transfer parsing
Jiang Guo, Wanxiang Che, David Yarowsky, Haifeng Wang, and Ting Liu. 2016 · 2016
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Simple and accurate dependency parsing using bidirectional LSTM feature representations
Eliyahu Kiperwasser and Yoav Goldberg. 2016 · 2016
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Opensubtitles2016: Extracting large parallel corpora from movie and tv subtitles
Pierre Lison and Jörg Tiedemann. 2016 · 2016
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The galactic dependencies treebanks: Getting more data by synthesizing new languages
Dingquan Wang and Jason Eisner. 2016 · 2016
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Cross-lingual word embeddings for low-resource language modeling
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 F. Liu, Matthew Peters, Michael Schmitz, and Luke Zettlemoyer. 2018 · 2018
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Learning word vectors for 157 languages
Edouard Grave, Piotr Bojanowski, Prakhar Gupta, Armand Joulin, and Tomas Mikolov. 2018a · 2018
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Non-adversarial unsupervised word translation
Yedid Hoshen and Lior Wolf. 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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Oliver Adams, Adam Makarucha, Graham Neubig, Steven Bird, and Trevor Cohn. 2017 · 2017
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Learning bilingual word embeddings with (almost) no bilingual data
Mikel Artetxe, Gorka Labaka, and Eneko Agirre. 2017 · 2017
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Evaluating layers of representation in neural machine translation on part-of-speech and semantic tagging tasks
Yonatan Belinkov, Lluís Màrquez, Hassan Sajjad, Nadir Durrani, Fahim Dalvi, and James Glass. 2017 · 2017
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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 D. Manning. 2017 · 2017
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Stanford’s graph-based neural dependency parser at the CoNLL 2017 Shared Task
Timothy Dozat, Peng Qi, and Christopher D. Manning. 2017 · 2017
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Learned in translation: Contextualized word vectors
Bryan McCann, James Bradbury, Caiming Xiong, and Richard Socher. 2017 · 2017
Cited alongside, same era.
Chao Jiang, Hsiang-Fu Yu, Cho-Jui Hsieh, and Kai-Wei Chang. 2018 · 2018
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Loss in translation: Learning bilingual word mapping with a retrieval criterion
Armand Joulin, Piotr Bojanowski, Tomas Mikolov, Hervé Jégou, and Edouard Grave. 2018 · 2018
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Unsupervised machine translation using monolingual corpora only
Guillaume Lample, Alexis Conneau, Ludovic Denoyer, and Marc’Aurelio Ranzato. 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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A multi-lingual multi-task architecture for low-resource sequence labeling
Ying Lin, Shengqi Yang, Veselin Stoyanov, and Heng Ji. 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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When and why are pre-trained word embeddings useful for neural machine translation?
Ye Qi, Devendra Sachan, Matthieu Felix, Sarguna Padmanabhan, and Graham Neubig. 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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CUNI x-ling: Parsing under-resourced languages in CoNLL 2018 UD Shared Task
Rudolf Rosa and David Mareček. 2018 · 2018
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82 treebanks, 34 models: Universal dependency parsing with multi-treebank models
Aaron Smith, Bernd Bohnet, Miryam de Lhoneux, Joakim Nivre, Yan Shao, and Sara Stymne. 2018a · 2018
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An investigation of the interactions between pre-trained word embeddings, character models and pos tags in dependency parsing
Aaron Smith, Miryam de Lhoneux, Sara Stymne, and Joakim Nivre. 2018b · 2018
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Improved dependency parsing using implicit word connections learned from unlabeled data
Wenhui Wang, Baobao Chang, and Mairgup Mansur. 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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Linguistic knowledge and transferability of contextual representations
Nelson F. Liu, Matt Gardner, Yonatan Belinkov, Matthew E. Peters, and Noah A. Smith. 2019 · 2019
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