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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 401–410 of 1773 papers

TitleStatusHype
Deep Neural Machine Translation with Linear Associative Unit—0
Better OOV Translation with Bilingual Terminology Mining—0
An Empirical Study of Document-to-document Neural Machine Translation—0
DeepSumm -- Deep Code Summaries using Neural Transformer Architecture—0
Defining Boundaries: The Impact of Domain Specification on Cross-Language and Cross-Domain Transfer in Machine Translation—0
Beyond BLEU:Training Neural Machine Translation with Semantic Similarity—0
Constraint Translation Candidates: A Bridge between Neural Query Translation and Cross-lingual Information Retrieval—0
Denoising Neural Machine Translation Training with Trusted Data and Online Data Selection—0
Dependency-Based Relative Positional Encoding for Transformer NMT—0
Constraining the Transformer NMT Model with Heuristic Grid Beam Search—0
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