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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 711–720 of 1773 papers

TitleStatusHype
Ancient-Modern Chinese Translation with a Large Training Dataset—0
Addressing Asymmetry in Multilingual Neural Machine Translation with Fuzzy Task Clustering—0
A Comprehensive Evaluation of Neural SPARQL Query Generation from Natural Language Questions—0
Cross-lingual Pre-training Based Transfer for Zero-shot Neural Machine Translation—0
Cross-lingual Human-Preference Alignment for Neural Machine Translation with Direct Quality Optimization—0
Cross-Corpora Evaluation and Analysis of Grammatical Error Correction Models --- Is Single-Corpus Evaluation Enough?—0
Automatic Bilingual Phrase Dictionary Construction from GIZA++ Output—0
An Augmented Translation Technique for low Resource language pair: Sanskrit to Hindi translation—0
CREAMT: Creativity and narrative engagement of literary texts translated by translators and NMT—0
Crafting Adversarial Examples for Neural Machine Translation—0
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