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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 1726–1750 of 1773 papers

TitleStatusHype
Neural Clinical Paraphrase Generation with Attention—0
Multilingual Disfluency Removal using NMT—0
Character-based Decoding in Tree-to-Sequence Attention-based Neural Machine Translation—0
Residual Stacking of RNNs for Neural Machine Translation—0
Topic-Informed Neural Machine Translation—0
Toward Multilingual Neural Machine Translation with Universal Encoder and Decoder—0
Google's Multilingual Neural Machine Translation System: Enabling Zero-Shot TranslationCode0
Neural Machine Translation with ReconstructionCode0
Validation of Tsallis Entropy In Inter-Modality Neuroimage Registration—0
Dual Learning for Machine TranslationCode0
Bridging Neural Machine Translation and Bilingual Dictionaries—0
Lexicons and Minimum Risk Training for Neural Machine Translation: NAIST-CMU at WAT2016—0
SYSTRAN's Pure Neural Machine Translation Systems—0
Interactive Attention for Neural Machine Translation—0
Pre-Translation for Neural Machine Translation—0
Neural Machine Translation Advised by Statistical Machine Translation—0
Fully Character-Level Neural Machine Translation without Explicit SegmentationCode0
Learning to Translate in Real-time with Neural Machine TranslationCode0
Bilingual Methods for Adaptive Training Data Selection for Machine Translation—0
Improving Neural Machine Translation on resource-limited pairs using auxiliary data of a third language—0
Google's Neural Machine Translation System: Bridging the Gap between Human and Machine TranslationCode0
Lattice-Based Recurrent Neural Network Encoders for Neural Machine Translation—0
One Sentence One Model for Neural Machine Translation—0
Factored Neural Machine Translation—0
Neural Machine Translation with Supervised Attention—0
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