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 731–740 of 1773 papers

TitleStatusHype
Coverage Embedding Models for Neural Machine Translation—0
Improving Low-Resource NMT through Relevance Based Linguistic Features Incorporation—0
Improving Machine Translation of Rare and Unseen Word Senses—0
Improving Autoregressive NMT with Non-Autoregressive Model—0
Improving Autoregressive NLP Tasks via Modular Linearized Attention—0
Cost-Effective Training in Low-Resource Neural Machine Translation—0
Improving Multilingual Sentence Embedding using Bi-directional Dual Encoder with Additive Margin Softmax—0
Automated Text Simplification as a Preprocessing Step for Machine Translation into an Under-resourced Language—0
An approach for mistranslation removal from popular dataset for Indic MT Task—0
Improvement in Machine Translation with Generative Adversarial Networks—0
Show:102550
← PrevPage 74 of 178Next →

No leaderboard results yet.