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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 961–970 of 1773 papers

TitleStatusHype
Reducing Hallucinations in Neural Machine Translation with Feature Attribution—0
Reducing Length Bias in Scoring Neural Machine Translation via a Causal Inference Method—0
Reducing Word Omission Errors in Neural Machine Translation: A Contrastive Learning Approach—0
Reference Network for Neural Machine Translation—0
Refining Source Representations with Relation Networks for Neural Machine Translation—0
Refining the state-of-the-art in Machine Translation, optimizing NMT for the JA <-> EN language pair by leveraging personal domain expertise—0
Regressing Word and Sentence Embeddings for Regularization of Neural Machine Translation—0
Regularization techniques for fine-tuning in neural machine translation—0
Regularized Context Gates on Transformer for Machine Translation—0
Regularizing Neural Machine Translation by Target-bidirectional Agreement—0
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