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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 326–350 of 1773 papers

TitleStatusHype
Fast Training of NMT Model with Data Sorting—0
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
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
Syntax-Aware Complex-Valued Neural Machine Translation—0
Pluggable Neural Machine Translation Models via Memory-augmented AdaptersCode0
xSIM++: An Improved Proxy to Bitext Mining Performance for Low-Resource Languages—0
Towards Accurate Translation via Semantically Appropriate Application of Lexical ConstraintsCode0
A Relaxed Optimization Approach for Adversarial Attacks against Neural Machine Translation Models—0
Learning Multilingual Sentence Representations with Cross-lingual Consistency RegularizationCode0
Textual Augmentation Techniques Applied to Low Resource Machine Translation: Case of Swahili—0
Rethinking Translation Memory Augmented Neural Machine Translation—0
On Search Strategies for Document-Level Neural Machine Translation—0
Improving Long Context Document-Level Machine Translation—0
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
Do GPTs Produce Less Literal Translations?Code0
On the Copying Problem of Unsupervised NMT: A Training Schedule with a Language Discriminator LossCode0
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