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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 781–790 of 1773 papers

TitleStatusHype
Zero-Shot Neural Machine Translation: Russian-Hindi @LoResMT 2020—0
Neural Machine Translation Doesn’t Translate Gender Coreference Right Unless You Make ItCode0
Zero-shot translation among Indian languages—0
Effective Use of Target-side Context for Neural Machine Translation—0
Knowledge Graph Enhanced Neural Machine Translation via Multi-task Learning on Sub-entity Granularity—0
A Document-Level Neural Machine Translation Model with Dynamic Caching Guided by Theme-Rheme InformationCode0
Neural Machine Translation Models with Back-Translation for the Extremely Low-Resource Indigenous Language BribriCode0
Improving Low-Resource NMT through Relevance Based Linguistic Features Incorporation—0
ContraCAT: Contrastive Coreference Analytical Templates for Machine Translation—0
Filtering Back-Translated Data in Unsupervised Neural Machine Translation—0
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