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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 331–340 of 1773 papers

TitleStatusHype
A Study of Reinforcement Learning for Neural Machine TranslationCode0
Attention Forcing for Machine TranslationCode0
Enhanced Neural Machine Translation by Learning from DraftCode0
Contextual Neural Machine Translation Improves Translation of Cataphoric PronounsCode0
Energy-Based Reranking: Improving Neural Machine Translation Using Energy-Based ModelsCode0
A Comparative Study of LLMs, NMT Models, and Their Combination in Persian-English Idiom TranslationCode0
Attentive fine-tuning of Transformers for Translation of low-resourced languages @LoResMT 2021Code0
Improving Neural Machine Translation with the Abstract Meaning Representation by Combining Graph and Sequence TransformersCode0
English-Japanese Neural Machine Translation with Encoder-Decoder-ReconstructorCode0
Enhancing Assamese NLP Capabilities: Introducing a Centralized Dataset RepositoryCode0
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