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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 901–910 of 1773 papers

TitleStatusHype
Using Context in Neural Machine Translation Training Objectives—0
Using Images to Improve Machine-Translating E-Commerce Product Listings.—0
Investigating Massive Multilingual Pre-Trained Machine Translation Models for Clinical Domain via Transfer Learning—0
Enhanced back-translation for low resource neural machine translation using self-training—0
Using Semantic Role Labeling to Improve Neural Machine Translation—0
Using Semantic Similarity as Reward for Reinforcement Learning in Sentence Generation—0
Using Spoken Word Posterior Features in Neural Machine Translation—0
Using Target-side Monolingual Data for Neural Machine Translation through Multi-task Learning—0
Utilizing Monolingual Data in NMT for Similar Languages: Submission to Similar Language Translation Task—0
Validation of Tsallis Entropy In Inter-Modality Neuroimage Registration—0
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