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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 501–510 of 1773 papers

TitleStatusHype
Multilingual Neural Machine Translation: Can Linguistic Hierarchies Help?—0
How should human translation coexist with NMT? Efficient tool for building high quality parallel corpus—0
Empirical Analysis of Korean Public AI Hub Parallel Corpora and in-depth Analysis using LIWC—0
Adaptive Bridge between Training and Inference for Dialogue—0
Continual Learning in Multilingual NMT via Language-Specific Embeddings—0
Multilingual Domain Adaptation for NMT: Decoupling Language and Domain Information with Adapters—0
Can Synthetic Translations Improve Bitext Quality?—0
A Two-Stage Curriculum Training Framework for NMT—0
Towards Making the Most of Multilingual Pretraining for Zero-Shot Neural Machine TranslationCode1
Multilingual Neural Machine Translation:Can Linguistic Hierarchies Help?—0
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