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Cross-lingual word vectors are typically obtained by fitting an orthogonal matrix that maps the entries of a bilingual dictionary from a source to a target vector space.
Tal Schuster, Ori Ram, Regina Barzilay, and Amir Globerson. 2019 · 1902
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A generalized solution of the orthogonal procrustes problem
Peter H Schönemann. 1966 · 1966
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The mathematics of statistical machine translation: Parameter estimation
Peter F Brown, Vincent J Della Pietra, Stephen A Della Pietra, and Robert L Mercer. 1993 · 1993
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Findings of the 2013 workshop on statistical machine translation
Ondrej Bojar, Christian Buck, Chris Callison-Burch, Christian Federmann, Barry Haddow, Philipp Koehn, Christof Monz, Matt Post, Radu Soricut, and Lucia Specia. 2013 · 2013
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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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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. 2014 · 2014
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Learning principled bilingual mappings of word embeddings while preserving monolingual invariance
Mikel Artetxe, Gorka Labaka, and Eneko Agirre. 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
Cited alongside, same era.
A simple but tough-to-beat baseline for sentence embeddings
Sanjeev Arora, Yingyu Liang, and Tengyu Ma. 2017 · 2017
Cited alongside, same era.
Enriching word vectors with subword information
Piotr Bojanowski, Edouard Grave, Armand Joulin, and Tomas Mikolov. 2017 · 2017
Cited alongside, same era.
Word translation without parallel data
Alexis Conneau, Guillaume Lample, Marc’Aurelio Ranzato, Ludovic Denoyer, and Hervé Jégou. 2017 · 2017
Later among the works it cites.
Offline bilingual word vectors, orthogonal transformations and the inverted softmax
Samuel L Smith, David HP Turban, Steven Hamblin, and Nils Y Hammerla. 2017 · 2017
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Evaluation of unsupervised compositional representations
Hanan Aldarmaki and Mona Diab. 2018 · 2018
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Unsupervised word mapping using structural similarities in monolingual embeddings
Hanan Aldarmaki, Mahesh Mohan, and Mona Diab. 2018 · 2018
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Evaluation of sentence embeddings in downstream and linguistic probing tasks
Christian S Perone, Roberto Silveira, and Thomas S Paula. 2018 · 2018
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Semeval-2017 task 2: Multilingual and cross-lingual semantic word similarity
Jose Camacho-Collados, Mohammad Taher Pilehvar, Nigel Collier, and Roberto Navigli. 2017 · 2017
Cited alongside, same era.
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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
Later among the works it cites.