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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 211–220 of 1773 papers

TitleStatusHype
An Empirical Study of Consistency Regularization for End-to-End Speech-to-Text TranslationCode0
Generalised Unsupervised Domain Adaptation of Neural Machine Translation with Cross-Lingual Data SelectionCode0
Better Neural Machine Translation by Extracting Linguistic Information from BERTCode0
Faithful Target Attribute Prediction in Neural Machine TranslationCode0
A Document-Level Neural Machine Translation Model with Dynamic Caching Guided by Theme-Rheme InformationCode0
First the worst: Finding better gender translations during beam searchCode0
Guided Alignment Training for Topic-Aware Neural Machine TranslationCode0
Guiding attention in Sequence-to-sequence models for Dialogue Act predictionCode0
Exploiting Social Media Content for Self-Supervised Style TransferCode0
Exploiting Out-of-Domain Parallel Data through Multilingual Transfer Learning for Low-Resource Neural Machine TranslationCode0
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