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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 1401–1410 of 1773 papers

TitleStatusHype
The Benefit of Pseudo-Reference Translations in Quality Estimation of MT Output—0
Extracting In-domain Training Corpora for Neural Machine Translation Using Data Selection Methods—0
The Sogou-TIIC Speech Translation System for IWSLT 2018—0
Coreference and Coherence in Neural Machine Translation: A Study Using Oracle Experiments—0
Multi-source transformer with combined losses for automatic post editing—0
Hunter NMT System for WMT18 Biomedical Translation Task: Transfer Learning in Neural Machine Translation—0
RTM results for Predicting Translation Performance—0
A Pronoun Test Suite Evaluation of the English--German MT Systems at WMT 2018—0
A Transformer-Based Multi-Source Automatic Post-Editing System—0
Findings of the WMT 2018 Shared Task on Automatic Post-Editing—0
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