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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 801–810 of 1773 papers

TitleStatusHype
A Hybrid Approach for Improved Low Resource Neural Machine Translation using Monolingual Data—0
Inference-only sub-character decomposition improves translation of unseen logographic characters—0
BERT-JAM: Boosting BERT-Enhanced Neural Machine Translation with Joint Attention—0
An Unsupervised method for OCR Post-Correction and Spelling Normalisation for FinnishCode1
Understanding Pure Character-Based Neural Machine Translation: The Case of Translating Finnish into English—0
PheMT: A Phenomenon-wise Dataset for Machine Translation Robustness on User-Generated ContentsCode1
Detecting Word Sense Disambiguation Biases in Machine Translation for Model-Agnostic Adversarial AttacksCode0
Emergent Communication Pretraining for Few-Shot Machine TranslationCode1
Investigating Catastrophic Forgetting During Continual Training for Neural Machine Translation—0
A Targeted Attack on Black-Box Neural Machine Translation with Parallel Data Poisoning—0
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