SOTAVerified

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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 671–680 of 1773 papers

TitleStatusHype
DC-MBR: Distributional Cooling for Minimum Bayesian Risk Decoding—0
Data Weighted Training Strategies for Grammatical Error Correction—0
Data Selection with Feature Decay Algorithms Using an Approximated Target Side—0
BERT-JAM: Boosting BERT-Enhanced Neural Machine Translation with Joint Attention—0
An Empirical Comparison of Simple Domain Adaptation Methods for Neural Machine Translation—0
Data Selection Curriculum for Neural Machine Translation—0
Data Scaling Laws in NMT: The Effect of Noise and Architecture—0
BERT Enhanced Neural Machine Translation and Sequence Tagging Model for Chinese Grammatical Error Diagnosis—0
Bering Lab’s Submissions on WAT 2021 Shared Task—0
Data Augmentation With Back translation for Low Resource languages: A case of English and Luganda—0
Show:102550
← PrevPage 68 of 178Next →

No leaderboard results yet.