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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 221–230 of 1773 papers

TitleStatusHype
Boosting Neural Machine Translation—0
Boosting Neural Machine Translation from Finnish to Northern Sámi with Rule-Based Backtranslation—0
An Empirical study of Unsupervised Neural Machine Translation: analyzing NMT output, model's behavior and sentences' contribution—0
Boosting Neural Networks to Decompile Optimized Binaries—0
BPE and CharCNNs for Translation of Morphology: A Cross-Lingual Comparison and Analysis—0
An In-depth Walkthrough on Evolution of Neural Machine Translation—0
Breaking the Corpus Bottleneck for Context-Aware Neural Machine Translation with Cross-Task Pre-training—0
An Empirical Study of Mini-Batch Creation Strategies for Neural Machine Translation—0
Bridging Dialects: Translating Standard Bangla to Regional Variants Using Neural Models—0
Addressing word-order Divergence in Multilingual Neural Machine Translation for extremely Low Resource Languages—0
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