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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 531–540 of 1773 papers

TitleStatusHype
Scaling Laws for Neural Machine Translation—0
Efficient Inference for Multilingual Neural Machine Translation—0
Non-Parametric Unsupervised Domain Adaptation for Neural Machine TranslationCode1
Fine Grained Human Evaluation for English-to-Chinese Machine Translation: A Case Study on Scientific Text—0
Multi-Sentence Resampling: A Simple Approach to Alleviate Dataset Length Bias and Beam-Search DegradationCode0
Evaluating Multiway Multilingual NMT in the Turkic LanguagesCode1
Contrastive Learning for Context-aware Neural Machine TranslationUsing Coreference Information—0
Attention Weights in Transformer NMT Fail Aligning Words Between Sequences but Largely Explain Model Predictions—0
Modeling Concentrated Cross-Attention for Neural Machine Translation with Gaussian Mixture Model—0
Improving Multilingual Translation by Representation and Gradient RegularizationCode1
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