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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 1–10 of 1773 papers

TitleStatusHype
Asymptotically Smaller Encodings for Graph Problems and Scheduling—0
ConECT Dataset: Overcoming Data Scarcity in Context-Aware E-Commerce MT—0
Enhancing Meme Token Market Transparency: A Multi-Dimensional Entity-Linked Address Analysis for Liquidity Risk Evaluation—0
In-Domain African Languages Translation Using LLMs and Multi-armed Bandits—0
THOR-MoE: Hierarchical Task-Guided and Context-Responsive Routing for Neural Machine Translation—0
Combining the Best of Both Worlds: A Method for Hybrid NMT and LLM Translation—0
Are We Paying Attention to Her? Investigating Gender Disambiguation and Attention in Machine TranslationCode0
Do Not Change Me: On Transferring Entities Without Modification in Neural Machine Translation -- a Multilingual PerspectiveCode0
TopicVD: A Topic-Based Dataset of Video-Guided Multimodal Machine Translation for DocumentariesCode0
Data Augmentation With Back translation for Low Resource languages: A case of English and Luganda—0
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