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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 451–460 of 1773 papers

TitleStatusHype
Domain Adaptation of NMT models for English-Hindi Machine Translation Task : AdapMT Shared Task ICON 2020—0
Domain adapted machine translation: What does catastrophic forgetting forget and why?—0
Domain Control for Neural Machine Translation—0
An In-depth Walkthrough on Evolution of Neural Machine Translation—0
Domain Informed Neural Machine Translation: Developing Translation Services for Healthcare Enterprise—0
Breaking the Corpus Bottleneck for Context-Aware Neural Machine Translation with Cross-Task Pre-training—0
A Multi-Task Architecture on Relevance-based Neural Query Translation—0
Do Multilingual Neural Machine Translation Models Contain Language Pair Specific Attention Heads?—0
Bridging Dialects: Translating Standard Bangla to Regional Variants Using Neural Models—0
Improving Neural Machine Translation with Pre-trained Representation—0
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