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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 1551–1560 of 1773 papers

TitleStatusHype
Syllable-Based Sequence-to-Sequence Speech Recognition with the Transformer in Mandarin ChineseCode0
Sparse Persistent RNNs: Squeezing Large Recurrent Networks On-Chip—0
Unsupervised Neural Machine Translation with Weight SharingCode0
A neural interlingua for multilingual machine translation—0
Phrase-Based & Neural Unsupervised Machine TranslationCode0
Fast Lexically Constrained Decoding with Dynamic Beam Allocation for Neural Machine Translation—0
When and Why are Pre-trained Word Embeddings Useful for Neural Machine Translation?Code0
Investigating Backtranslation in Neural Machine Translation—0
Improving Character-based Decoding Using Target-Side Morphological Information for Neural Machine Translation—0
Near Human-Level Performance in Grammatical Error Correction with Hybrid Machine Translation—0
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