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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 1511–1520 of 1773 papers

TitleStatusHype
When and Why are Pre-trained Word Embeddings Useful for Neural Machine Translation?Code0
When and Why is Document-level Context Useful in Neural Machine Translation?Code0
How do lexical semantics affect translation? An empirical studyCode0
MTCue: Learning Zero-Shot Control of Extra-Textual Attributes by Leveraging Unstructured Context in Neural Machine TranslationCode0
Domain Generalisation of NMT: Fusing Adapters with Leave-One-Domain-Out TrainingCode0
How Grammatical is Character-level Neural Machine Translation? Assessing MT Quality with Contrastive Translation PairsCode0
Verdi: Quality Estimation and Error Detection for Bilingual CorporaCode0
Optimal Transport for Unsupervised Hallucination Detection in Neural Machine TranslationCode0
Unsupervised Question Answering by Cloze TranslationCode0
Optimizing the Training Schedule of Multilingual NMT using Reinforcement LearningCode0
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