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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 1081–1090 of 1773 papers

TitleStatusHype
Tailoring Neural Architectures for Translating from Morphologically Rich Languages—0
Taking Actions Separately: A Bidirectionally-Adaptive Transfer Learning Method for Low-Resource Neural Machine Translation—0
Target Conditioned Sampling: Optimizing Data Selection for Multilingual Neural Machine Translation—0
Target Conditioning for One-to-Many Generation—0
A Targeted Attack on Black-Box Neural Machine Translation with Parallel Data Poisoning—0
Temporal Attention Model for Neural Machine Translation—0
Tencent AI Lab Machine Translation Systems for WMT20 Chat Translation Task—0
TencentFmRD Neural Machine Translation for WMT18—0
Terminology-Aware Segmentation and Domain Feature for the WMT19 Biomedical Translation Task—0
Terminology-Aware Sentence Mining for NMT Domain Adaptation: ADAPT’s Submission to the Adap-MT 2020 English-to-Hindi AI Translation Shared Task—0
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