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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 471–480 of 1773 papers

TitleStatusHype
Finding the Right Recipe for Low Resource Domain Adaptation in Neural Machine Translation—0
Fast-Paced Improvements to Named Entity Handling for Neural Machine Translation—0
Multilingual Neural Machine Translation With the Right Amount of Sharing—0
Dynamic Adaptation of Neural Machine-Translation Systems Through Translation Exemplars—0
MultitraiNMT Erasmus+ project: Machine Translation Training for multilingual citizens (multitrainmt.eu)—0
Achievements of the PRINCIPLE Project: Promoting MT for Croatian, Icelandic, Irish and Norwegian—0
Latest Development in the FoTran Project – Scaling Up Language Coverage in Neural Machine Translation Using Distributed Training with Language-Specific Components—0
BERTology for Machine Translation: What BERT Knows about Linguistic Difficulties for Translation—0
The Multilingual Microblog Translation Corpus: Improving and Evaluating Translation of User-Generated Text—0
Passing Parser Uncertainty to the Transformer. Labeled Dependency Distributions for Neural Machine Translation.—0
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