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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 1291–1300 of 1773 papers

TitleStatusHype
Adaptation and Combination of NMT Systems: The KIT Translation Systems for IWSLT 2016—0
Adaptation of Machine Translation Models with Back-translated Data using Transductive Data Selection Methods—0
Adapting Multilingual NMT to Extremely Low Resource Languages FBK’s Participation in the Basque-English Low-Resource MT Task, IWSLT 2018—0
Adaptive Bridge between Training and Inference for Dialogue—0
Adaptive Bridge between Training and Inference for Dialogue Generation—0
Adaptive Knowledge Sharing in Multi-Task Learning: Improving Low-Resource Neural Machine Translation—0
Adaptively Scheduled Multitask Learning: The Case of Low-Resource Neural Machine Translation—0
Adaptive Multi-pass Decoder for Neural Machine Translation—0
Addressing Asymmetry in Multilingual Neural Machine Translation with Fuzzy Task Clustering—0
Addressing Posterior Collapse with Mutual Information for Improved Variational Neural Machine Translation—0
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