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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 21–30 of 1773 papers

TitleStatusHype
A Survey on Non-Autoregressive Generation for Neural Machine Translation and BeyondCode1
Asynchronous Bidirectional Decoding for Neural Machine TranslationCode1
Domain Adaptation of Neural Machine Translation by Lexicon InductionCode1
AutoMoE: Heterogeneous Mixture-of-Experts with Adaptive Computation for Efficient Neural Machine TranslationCode1
BERT, mBERT, or BiBERT? A Study on Contextualized Embeddings for Neural Machine TranslationCode1
Beyond Decoder-only: Large Language Models Can be Good Encoders for Machine TranslationCode1
Bi-SimCut: A Simple Strategy for Boosting Neural Machine TranslationCode1
Breaking the Representation Bottleneck of Chinese Characters: Neural Machine Translation with Stroke Sequence ModelingCode1
Can Automatic Post-Editing Improve NMT?Code1
Automatic Machine Translation Evaluation in Many Languages via Zero-Shot ParaphrasingCode1
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