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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 501–510 of 1773 papers

TitleStatusHype
EMMeTT: Efficient Multimodal Machine Translation Training—0
Empirical Analysis of Korean Public AI Hub Parallel Corpora and in-depth Analysis using LIWC—0
A Comparison of Data Filtering Methods for Neural Machine Translation—0
Empirical Evaluation of Active Learning Techniques for Neural MT—0
Enabling Multi-Source Neural Machine Translation By Concatenating Source Sentences In Multiple Languages—0
Capturing document context inside sentence-level neural machine translation models with self-training—0
Encoders Help You Disambiguate Word Senses in Neural Machine Translation—0
Encoding Gated Translation Memory into Neural Machine Translation—0
Encodings of Source Syntax: Similarities in NMT Representations Across Target Languages—0
Conflict as an Inverse of Attention in Sequence Relationship—0
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