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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 171–180 of 1773 papers

TitleStatusHype
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
TopicVD: A Topic-Based Dataset of Video-Guided Multimodal Machine Translation for DocumentariesCode0
Do Not Change Me: On Transferring Entities Without Modification in Neural Machine Translation -- a Multilingual PerspectiveCode0
Data Augmentation With Back translation for Low Resource languages: A case of English and Luganda—0
AI agents may be worth the hype but not the resources (yet): An initial exploration of machine translation quality and costs in three language pairs in the legal and news domains—0
Calibrating Translation Decoding with Quality Estimation on LLMsCode0
Is LLM the Silver Bullet to Low-Resource Languages Machine Translation?—0
Beyond Vanilla Fine-Tuning: Leveraging Multistage, Multilingual, and Domain-Specific Methods for Low-Resource Machine Translation—0
Contextual Cues in Machine Translation: Investigating the Potential of Multi-Source Input Strategies in LLMs and NMT Systems—0
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