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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 951–960 of 1773 papers

TitleStatusHype
Question Answering over Knowledge Graphs with Neural Machine Translation and Entity Linking—0
Rank-One Editing of Encoder-Decoder Models—0
Reconsidering SMT Over NMT for Closely Related Languages: A Case Study of Persian-Hindi Pair—0
Recurrent Graph Syntax Encoder for Neural Machine Translation—0
Recurrent Stacking of Layers for Compact Neural Machine Translation Models—0
Recurrent Stacking of Layers in Neural Networks: An Application to Neural Machine Translation—0
Recycling a Pre-trained BERT Encoder for Neural Machine Translation—0
Reduce Indonesian Vocabularies with an Indonesian Sub-word Separator—0
Reducing Disambiguation Biases in NMT by Leveraging Explicit Word Sense Information—0
Reducing Gender Bias in Machine Translation through Counterfactual Data Generation—0
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