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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 541–550 of 1773 papers

TitleStatusHype
The Ecological Footprint of Neural Machine Translation SystemsCode0
Learning How to Translate North Korean through South Korean—0
On the Effectiveness of Quasi Character-Level Models for Machine Translation—0
What Role Does BERT Play in the Neural Machine Translation Encoder?—0
Document-level Neural Machine Translation Using Dependency RST Structure—0
Bi-SimCut: A Simple Strategy for Boosting Neural Machine Translation—0
Patching Leaks in the Charformer for Generative Tasks—0
On Synthetic Data for Back Translation—0
When do Contrastive Word Alignments Improve Many-to-many Neural Machine Translation?—0
Neighbors Are Not Strangers: Improving Non-Autoregressive Translation under Low-Frequency Lexical Constraints—0
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