Papers with pairwise adaptation

1 papers
Domain Adaptation of Neural Machine Translation by Lexicon Induction (P19-1)

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Challenge: Neural machine translation (NMT) is sensitive to domain shift, resulting in failure for sentences with large numbers of unknown words and lack of supervision for domain-specific words.
Approach: They propose an unsupervised method which fine-tunes a pre-trained out-of-domain NMT model using a pseudo-in-domain corpus.
Outcome: The proposed method improves in five domains without using in-domain parallel sentences and up to 2 BLEU over strong back-translation baselines.

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