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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 511–520 of 1773 papers

TitleStatusHype
Extract and Attend: Improving Entity Translation in Neural Machine Translation—0
A Comparison of Data Filtering Methods for Neural Machine Translation—0
Conflict as an Inverse of Attention in Sequence Relationship—0
Adaptive Bridge between Training and Inference for Dialogue—0
Evaluating Low-Resource Machine Translation between Chinese and Vietnamese with Back-Translation—0
Confidence Based Bidirectional Global Context Aware Training Framework for Neural Machine Translation—0
ConECT Dataset: Overcoming Data Scarcity in Context-Aware E-Commerce MT—0
A Teacher-Student Framework for Zero-Resource Neural Machine Translation—0
Conditional Variational Autoencoder for Neural Machine Translation—0
Concept Equalization to Guide Correct Training of Neural Machine Translation—0
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