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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 376–400 of 1773 papers

TitleStatusHype
Towards Reliable Neural Machine Translation with Consistency-Aware Meta-Learning—0
Preparing the Vuk'uzenzele and ZA-gov-multilingual South African multilingual corporaCode0
Exploiting Language Relatedness in Machine Translation Through Domain Adaptation Techniques—0
Targeted Adversarial Attacks against Neural Machine TranslationCode0
A Systematic Analysis of Vocabulary and BPE Settings for Optimal Fine-tuning of NMT: A Case Study of In-domain Translation—0
Are Character-level Translations Worth the Wait? Comparing ByT5 and mT5 for Machine TranslationCode0
Federated Nearest Neighbor Machine Translation—0
Generalization algorithm of multimodal pre-training model based on graph-text self-supervised training—0
TransFool: An Adversarial Attack against Neural Machine Translation ModelsCode0
Attention Link: An Efficient Attention-Based Low Resource Machine Translation Architecture—0
A Multi-task Multi-stage Transitional Training Framework for Neural Chat Translation—0
Improving Machine Translation with Phrase Pair Injection and Corpus Filtering—0
Prompting Neural Machine Translation with Translation Memories—0
Building a Parallel Corpus and Training Translation Models Between Luganda and English—0
Boosting Neural Networks to Decompile Optimized Binaries—0
Active Learning for Neural Machine TranslationCode0
Optimal Transport for Unsupervised Hallucination Detection in Neural Machine TranslationCode0
Synthetic Pre-Training Tasks for Neural Machine Translation—0
Continual Knowledge Distillation for Neural Machine TranslationCode0
Better Datastore, Better Translation: Generating Datastores from Pre-Trained Models for Nearest Neural Machine Translation—0
P-Transformer: Towards Better Document-to-Document Neural Machine TranslationCode0
Who Evaluates the Evaluators? On Automatic Metrics for Assessing AI-based Offensive Code Generators—0
DC-MBR: Distributional Cooling for Minimum Bayesian Risk Decoding—0
Word Alignment in the Era of Deep Learning: A Tutorial—0
PhraseTransformer: An Incorporation of Local Context Information into Sequence-to-sequence Semantic ParsingCode0
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