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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 1241–1250 of 1773 papers

TitleStatusHype
English-Czech Systems in WMT19: Document-Level Transformer—0
Joey NMT: A Minimalist NMT Toolkit for NovicesCode0
MacNet: Transferring Knowledge from Machine Comprehension to Sequence-to-Sequence Models—0
Learning the Relation between Code Features and Code Transforms with Structured PredictionCode0
Structure-Invariant Testing for Machine TranslationCode1
Understanding Neural Machine Translation by Simplification: The Case of Encoder-free Models—0
Hierarchical Sequence to Sequence Voice Conversion with Limited Data—0
Massively Multilingual Neural Machine Translation in the Wild: Findings and Challenges—0
Modelling the Socialization of Creative Agents in a Master-Apprentice Setting: The Case of Movie Title Puns—0
Exploiting Out-of-Domain Parallel Data through Multilingual Transfer Learning for Low-Resource Neural Machine TranslationCode0
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