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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 1031–1040 of 1773 papers

TitleStatusHype
Improving Character-based Decoding Using Target-Side Morphological Information for Neural Machine Translation—0
Improving Character-level Japanese-Chinese Neural Machine Translation with Radicals as an Additional Input Feature—0
Improving Context-aware Neural Machine Translation with Target-side Context—0
Improving Document-Level Neural Machine Translation with Domain Adaptation—0
Improving English to Sinhala Neural Machine Translation using Part-of-Speech Tag—0
Improving Japanese-to-English Neural Machine Translation by Paraphrasing the Target Language—0
Improving Long Context Document-Level Machine Translation—0
Improving Low-Resource NMT through Relevance Based Linguistic Features Incorporation—0
Improving Machine Translation of Rare and Unseen Word Senses—0
Improving Machine Translation with Phrase Pair Injection and Corpus Filtering—0
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