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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

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Showing 171–180 of 1773 papers

TitleStatusHype
SOTASTREAM: A Streaming Approach to Machine Translation TrainingCode1
Evaluating and Optimizing the Effectiveness of Neural Machine Translation in Supporting Code Retrieval Models: A Study on the CAT Benchmark—0
Character-level NMT and language similarity—0
SelfSeg: A Self-supervised Sub-word Segmentation Method for Neural Machine Translation—0
Joint Dropout: Improving Generalizability in Low-Resource Neural Machine Translation through Phrase Pair VariablesCode0
Syntax-Aware Complex-Valued Neural Machine Translation—0
Improving End-to-End Speech Translation by Imitation-Based Knowledge Distillation with Synthetic TranscriptsCode0
Enhancing Supervised Learning with Contrastive Markings in Neural Machine Translation Training—0
Pluggable Neural Machine Translation Models via Memory-augmented AdaptersCode0
xSIM++: An Improved Proxy to Bitext Mining Performance for Low-Resource Languages—0
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