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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 591–600 of 1773 papers

TitleStatusHype
A Compact and Language-Sensitive Multilingual Translation Method—0
From Balustrades to Pierre Vinken: Looking for Syntax in Transformer Self-Attentions—0
Fusing Recency into Neural Machine Translation with an Inter-Sentence Gate Model—0
FBK’s Neural Machine Translation Systems for IWSLT 2016—0
Comparative Evaluation of NMT with Established SMT Programs—0
FeatureBART: Feature Based Sequence-to-Sequence Pre-Training for Low-Resource NMT—0
Feature-rich NMT and SMT post-edited corpora for productivity and evaluation tasks with a subset of MQM-annotated data—0
Federated Nearest Neighbor Machine Translation—0
Exploiting Multilingualism through Multistage Fine-Tuning for Low-Resource Neural Machine Translation—0
Exploiting Multilingualism in Low-resource Neural Machine Translation via Adversarial Learning—0
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