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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 176–200 of 1773 papers

TitleStatusHype
Improving End-to-End Speech Translation by Imitation-Based Knowledge Distillation with Synthetic TranscriptsCode0
Syntax-Aware Complex-Valued Neural Machine Translation—0
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 LanguagesCode0
Towards Accurate Translation via Semantically Appropriate Application of Lexical ConstraintsCode0
A Relaxed Optimization Approach for Adversarial Attacks against Neural Machine Translation Models—0
Textual Augmentation Techniques Applied to Low Resource Machine Translation: Case of Swahili—0
Learning Multilingual Sentence Representations with Cross-lingual Consistency RegularizationCode0
Rethinking Translation Memory Augmented Neural Machine Translation—0
Improving Long Context Document-Level Machine Translation—0
On Search Strategies for Document-Level Neural Machine Translation—0
MobileNMT: Enabling Translation in 15MB and 30msCode1
Extract and Attend: Improving Entity Translation in Neural Machine Translation—0
Leveraging Auxiliary Domain Parallel Data in Intermediate Task Fine-tuning for Low-resource TranslationCode0
Assessing the Importance of Frequency versus Compositionality for Subword-based Tokenization in NMTCode0
How Does Pretraining Improve Discourse-Aware Translation?—0
Translation-Enhanced Multilingual Text-to-Image Generation—0
Augmenting Large Language Model Translators via Translation Memories—0
CODET: A Benchmark for Contrastive Dialectal Evaluation of Machine Translation—0
Bridging the Domain Gaps in Context Representations for k-Nearest Neighbor Neural Machine TranslationCode1
On the Copying Problem of Unsupervised NMT: A Training Schedule with a Language Discriminator LossCode0
Gender Lost In Translation: How Bridging The Gap Between Languages Affects Gender Bias in Zero-Shot Multilingual TranslationCode0
Songs Across Borders: Singable and Controllable Neural Lyric TranslationCode1
Do GPTs Produce Less Literal Translations?Code0
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