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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 311–320 of 1773 papers

TitleStatusHype
On the Effectiveness of Quasi Character-Level Models for Machine Translation—0
English-Russian Data Augmentation for Neural Machine Translation—0
A Comparison of Data Filtering Methods for Neural Machine Translation—0
The impact of translation competence on error recognition of neural MT—0
All You Need is Source! A Study on Source-based Quality Estimation for Neural Machine Translation—0
Discourse Cohesion Evaluation for Document-Level Neural Machine Translation—0
How Effective is Byte Pair Encoding for Out-Of-Vocabulary Words in Neural Machine Translation?—0
Looking for a Needle in a Haystack: A Comprehensive Study of Hallucinations in Neural Machine TranslationCode1
Benchmarking Azerbaijani Neural Machine Translation—0
Multimodal Neural Machine Translation with Search Engine Based Image Retrieval—0
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