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 1501–1510 of 1773 papers

TitleStatusHype
A Deep Learning Based Approach to Transliteration—0
Adaptive Knowledge Sharing in Multi-Task Learning: Improving Low-Resource Neural Machine Translation—0
OpenNMT System Description for WNMT 2018: 800 words/sec on a single-core CPU—0
Neural Machine Translation with Key-Value Memory-Augmented Attention—0
Neural Machine Translation for Low Resource Languages using Bilingual Lexicon Induced from Comparable Corpora—0
On Adversarial Examples for Character-Level Neural Machine TranslationCode0
Learning from Chunk-based Feedback in Neural Machine Translation—0
A Comparison of Transformer and Recurrent Neural Networks on Multilingual Neural Machine Translation—0
Morphological and Language-Agnostic Word Segmentation for NMTCode0
An Evaluation of Neural Machine Translation Models on Historical Spelling NormalizationCode0
Show:102550
← PrevPage 151 of 178Next →

No leaderboard results yet.