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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

Showing 11011125 of 1773 papers

TitleStatusHype
Exploiting Multilingualism through Multistage Fine-Tuning for Low-Resource Neural Machine Translation0
Hierarchical Modeling of Global Context for Document-Level Neural Machine Translation0
Exploiting Monolingual Data at Scale for Neural Machine Translation0
On the Linguistic Representational Power of Neural Machine Translation Models0
Unsupervised Neural Machine Translation with Future Rewarding0
On the Relation between Position Information and Sentence Length in Neural Machine Translation0
Synchronously Generating Two Languages with Interactive Decoding0
Improving Neural Machine Translation by Achieving Knowledge Transfer with Sentence Alignment Learning0
Recycling a Pre-trained BERT Encoder for Neural Machine Translation0
English to Hindi Multi-modal Neural Machine Translation and Hindi Image Captioning0
Mixed Multi-Head Self-Attention for Neural Machine Translation0
Learning to Generate Word- and Phrase-Embeddings for Efficient Phrase-Based Neural Machine Translation0
English-Myanmar Supervised and Unsupervised NMT: NICT's Machine Translation Systems at WAT-20190
Empirical Evaluation of Active Learning Techniques for Neural MT0
NICT's participation to WAT 2019: Multilingualism and Multi-step Fine-Tuning for Low Resource NMT0
KNU-HYUNDAI's NMT system for Scientific Paper and Patent Tasks onWAT 20190
Combining Translation Memory with Neural Machine Translation0
Japanese-Russian TMU Neural Machine Translation System using Multilingual Model for WAT 20190
Controlling Japanese Honorifics in English-to-Japanese Neural Machine Translation0
Supervised and Unsupervised Machine Translation for Myanmar-English and Khmer-English0
Zero-Resource Neural Machine Translation with Monolingual Pivot Data0
Sarah's Participation in WAT 20190
Data augmentation using back-translation for context-aware neural machine translation0
Adaptively Scheduled Multitask Learning: The Case of Low-Resource Neural Machine Translation0
Analysing concatenation approaches to document-level NMT in two different domains0
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