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NMT

Neural machine translation is an approach to machine translation that uses an artificial neural network to predict the likelihood of a sequence of words, typically modeling entire sentences in a single integrated model.

Papers

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Showing 501–510 of 1773 papers

TitleStatusHype
SALTED: A Framework for SAlient Long-Tail Translation Error Detection—0
Exploiting Social Media Content for Self-Supervised Style TransferCode0
Data Augmentation to Address Out-of-Vocabulary Problem in Low-Resource Sinhala-English Neural Machine Translation—0
Controlling Formality in Low-Resource NMT with Domain Adaptation and Re-Ranking: SLT-CDT-UoS at IWSLT2022—0
AdMix: A Mixed Sample Data Augmentation Method for Neural Machine Translation—0
Training Mixed-Domain Translation Models via Federated Learning—0
Jam or Cream First? Modeling Ambiguity in Neural Machine Translation with SCONES—0
The Implicit Length Bias of Label Smoothing on Beam Search Decoding—0
Translation Techies @DravidianLangTech-ACL2022-Machine Translation in Dravidian Languages—0
Machine Translation for Livonian: Catering to 20 Speakers—0
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