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 951–960 of 1773 papers

TitleStatusHype
On the Sparsity of Neural Machine Translation Models—0
Iterative Domain-Repaired Back-Translation—0
Why Skip If You Can Combine: A Simple Knowledge Distillation Technique for Intermediate LayersCode0
Vector-Vector-Matrix Architecture: A Novel Hardware-Aware Framework for Low-Latency Inference in NLP Applications—0
Converting the Point of View of Messages Spoken to Virtual AssistantsCode0
Multi-task Learning for Multilingual Neural Machine Translation—0
Adversarial Grammatical Error Correction—0
Improving Target-side Lexical Transfer in Multilingual Neural Machine Translation—0
A Mixed Learning Objective for Neural Machine Translation—0
Low-Resource NMT: an Empirical Study on the Effect of Rich Morphological Word Segmentation on InuktitutCode0
Show:102550
← PrevPage 96 of 178Next →

No leaderboard results yet.