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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 741–750 of 1773 papers

TitleStatusHype
A Simple and General Strategy for Referential Problem in Low-Resource Neural Machine Translation—0
FGraDA: A Dataset and Benchmark for Fine-Grained Domain Adaptation in Machine TranslationCode0
Neural Machine Translation: A Review of Methods, Resources, and Tools—0
Revisiting Robust Neural Machine Translation: A Transformer Case Study—0
Synthetic Source Language Augmentation for Colloquial Neural Machine Translation—0
Learning Light-Weight Translation Models from Deep TransformerCode1
Why Neural Machine Translation Prefers Empty Outputs—0
Domain Adaptation of NMT models for English-Hindi Machine Translation Task at AdapMT ICON 2020—0
Modeling Homophone Noise for Robust Neural Machine Translation—0
Approches quantitatives de l'analyse des prédictions en traduction automatique neuronale (TAN)—0
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