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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 1051–1060 of 1773 papers

TitleStatusHype
Source and Target Bidirectional Knowledge Distillation for End-to-end Speech Translation—0
SOURCE: SOURce-Conditional Elmo-style Model for Machine Translation Quality Estimation—0
Sparse and Decorrelated Representations for Stable Zero-shot NMT—0
Sparse Persistent RNNs: Squeezing Large Recurrent Networks On-Chip—0
Specializing Multi-domain NMT via Penalizing Low Mutual Information—0
Speeding Up Neural Machine Translation Decoding by Shrinking Run-time Vocabulary—0
Spiral Language Modeling—0
SSN-NLP at SemEval-2020 Task 4: Text Classification and Generation on Common Sense Context Using Neural Networks—0
Start-Before-End and End-to-End: Neural Speech Translation by AppTek and RWTH Aachen University—0
Studying The Impact Of Document-level Context On Simultaneous Neural Machine Translation—0
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