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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 521–530 of 1773 papers

TitleStatusHype
When do Contrastive Word Alignments Improve Many-to-many Neural Machine Translation?—0
DaLC: Domain Adaptation Learning Curve Prediction for Neural Machine Translation—0
Generating Authentic Adversarial Examples beyond Meaning-preserving with Doubly Round-trip TranslationCode0
Dynamic Position Encoding for Transformers—0
Efficient Cluster-Based k-Nearest-Neighbor Machine TranslationCode0
A Token-level Contrastive Framework for Sign Language TranslationCode0
C-NMT: A Collaborative Inference Framework for Neural Machine Translation—0
Can NMT Understand Me? Towards Perturbation-based Evaluation of NMT Models for Code Generation—0
Data Selection Curriculum for Neural Machine Translation—0
Universal Conditional Masked Language Pre-training for Neural Machine Translation—0
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