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 651–660 of 1773 papers

TitleStatusHype
Dependency-Based Self-Attention for Transformer NMT—0
Dependency-Based Relative Positional Encoding for Transformer NMT—0
Denoising Neural Machine Translation Training with Trusted Data and Online Data Selection—0
An Empirical Study of Mini-Batch Creation Strategies for Neural Machine Translation—0
Addressing word-order Divergence in Multilingual Neural Machine Translation for extremely Low Resource Languages—0
Defining Boundaries: The Impact of Domain Specification on Cross-Language and Cross-Domain Transfer in Machine Translation—0
Beyond BLEU:Training Neural Machine Translation with Semantic Similarity—0
DeepSumm -- Deep Code Summaries using Neural Transformer Architecture—0
An Empirical Study of Document-to-document Neural Machine Translation—0
Deep Neural Machine Translation with Linear Associative Unit—0
Show:102550
← PrevPage 66 of 178Next →

No leaderboard results yet.