Papers by Pierre Foret

1 papers
A Multilingual View of Unsupervised Machine Translation (2020.findings-emnlp)

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Challenge: Empirically, we show that our approach results in higher BLEU scores over state-of-the-art unsupervised models on the WMT’14 English-French, WMT'16 English-German, and WMT‘16 English–Romanian datasets in most directions.
Approach: They propose a probabilistic framework for multilingual neural machine translation that encompasses supervised and unsupervised setups, focusing on unsupervised translation.
Outcome: The proposed framework achieves higher BLEU scores than state-of-the-art unsupervised models on the WMT’14 English-French, WMT'16 English-German, and WMT‘16 English–Romanian datasets in most directions.

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