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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 1151–1160 of 1773 papers

TitleStatusHype
When and Why is Document-level Context Useful in Neural Machine Translation?Code0
Machine Translation for Machines: the Sentiment Classification Use Case—0
Interrogating the Explanatory Power of Attention in Neural Machine TranslationCode0
Regressing Word and Sentence Embeddings for Regularization of Neural Machine Translation—0
On the use of BERT for Neural Machine Translation—0
Selecting Artificially-Generated Sentences for Fine-Tuning Neural Machine Translation—0
Large-scale Pretraining for Neural Machine Translation with Tens of Billions of Sentence Pairs—0
Self-Induced Curriculum Learning in Neural Machine Translation—0
Context Based Machine Translation With Recurrent Neural Network For English-Amharic Translation—0
Efficiently Reusing Old Models Across Languages via Transfer Learning—0
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