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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 571–580 of 1773 papers

TitleStatusHype
Improvement in Machine Translation with Generative Adversarial Networks—0
Deps-SAN: Neural Machine Translation with Dependency-Scaled Self-Attention Network—0
Causal Transformers: Improving the Robustness on Spurious Correlations—0
A Primer in NMTology: What we have understood about NMT—0
A Neural Approach to KGQA via SPARQL Silhouette Generation—0
Dict-NMT: Bilingual Dictionary based NMT for Extremely Low Resource Languages—0
Integrating Vectorized Lexical Constraints for Neural Machine Translation—0
An Empirical Study of Document-to-document Neural Machine Translation—0
What Works and Doesn't Work, A Deep Decoder for Neural Machine Translation—0
Research on the Evaluation of Token Imbalance Degree of NMT Corpus—0
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