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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 1481–1490 of 1773 papers

TitleStatusHype
NICT Self-Training Approach to Neural Machine Translation at NMT-2018—0
Regularized Training Objective for Continued Training for Domain Adaptation in Neural Machine TranslationCode0
Learning Distributional Token Representations from Visual Features—0
Unsupervised Source Hierarchies for Low-Resource Neural Machine Translation—0
Moon IME: Neural-based Chinese Pinyin Aided Input Method with Customizable Association—0
How Much Attention Do You Need? A Granular Analysis of Neural Machine Translation Architectures—0
Forest-Based Neural Machine Translation—0
Are BLEU and Meaning Representation in Opposition?—0
SuperNMT: Neural Machine Translation with Semantic Supersenses and Syntactic Supertags—0
Adaptive Knowledge Sharing in Multi-Task Learning: Improving Low-Resource Neural Machine Translation—0
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