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The performance of Neural Machine Translation (NMT) systems often suffers in low-resource scenarios where sufficiently large-scale parallel corpora cannot be obtained.
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Mitchell P Marcus, Mary Ann Marcinkiewicz, and Beatrice Santorini. 1993 · 1993
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Tomas Mikolov, Ilya Sutskever, Kai Chen, Greg S Corrado, and Jeff Dean. 2013 · 2013
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Di He, Yingce Xia, Tao Qin, Liwei Wang, Nenghai Yu, Tieyan Liu, and Wei-Ying Ma. 2016 · 2016
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Google’s multilingual neural machine translation system: Enabling zero-shot translation
Unsupervised neural machine translation
Mikel Artetxe, Gorka Labaka, Eneko Agirre, and Kyunghyun Cho. 2017 · 2017
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Word translation without parallel data
Alexis Conneau, Guillaume Lample, Marc’Aurelio Ranzato, Ludovic Denoyer, and Hervé Jégou. 2017 · 2017
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Stronger baselines for trustable results in neural machine translation
Michael Denkowski and Graham Neubig. 2017 · 2017
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Monolingual embeddings for low resourced neural machine translation
Mattia Antonino Di Gangi and Marcello Federico. 2017 · 2017
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Advances in pre-training distributed word representations
Tomas Mikolov, Edouard Grave, Piotr Bojanowski, Christian Puhrsch, and Armand Joulin. 2017 · 2017
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A bag of useful tricks for practical neural machine translation: Embedding layer initialization and large batch size
Masato Neishi, Jin Sakuma, Satoshi Tohda, Shonosuke Ishiwatari, Naoki Yoshinaga, and Masashi Toyoda. 2017 · 2017
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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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XNMT: The extensible neural machine translation toolkit
Graham Neubig, Matthias Sperber, Xinyi Wang, Matthieu Felix, Austin Matthews, Sarguna Padmanabhan, Ye Qi, Devendra Singh Sachan, Philip Arthur, Pierre Godard, John Hewitt, Rachid Riad, and Liming Wang. 2018 · 2018
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