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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 451–475 of 1773 papers

TitleStatusHype
All You Need is Source! A Study on Source-based Quality Estimation for Neural Machine Translation—0
Discourse Cohesion Evaluation for Document-Level Neural Machine Translation—0
How Effective is Byte Pair Encoding for Out-Of-Vocabulary Words in Neural Machine Translation?—0
Benchmarking Azerbaijani Neural Machine Translation—0
Multimodal Neural Machine Translation with Search Engine Based Image Retrieval—0
Learning to translate by learning to communicateCode0
Sockeye 3: Fast Neural Machine Translation with PyTorch—0
UM4: Unified Multilingual Multiple Teacher-Student Model for Zero-Resource Neural Machine TranslationCode0
End-to-End Simultaneous Speech Translation with Pretraining and Distillation: Huawei Noah’s System for AutoSimTranS 2022—0
Bridging the Gap between Training and Inference: Multi-Candidate Optimization for Diverse Neural Machine TranslationCode0
Reduce Indonesian Vocabularies with an Indonesian Sub-word Separator—0
Improving Neural Machine Translation with the Abstract Meaning Representation by Combining Graph and Sequence TransformersCode0
Cross-Language Transfer of High-Quality Annotations: Combining Neural Machine Translation with Cross-Linguistic Span Alignment to Apply NER to Clinical Texts in a Low-Resource LanguageCode0
Reducing Disambiguation Biases in NMT by Leveraging Explicit Word Sense Information—0
Unified NMT models for the Indian subcontinent, transcending script-barriers—0
Code Translation with Compiler Representations—0
Probing Causes of Hallucinations in Neural Machine Translations—0
FreeTransfer-X: Safe and Label-Free Cross-Lingual Transfer from Off-the-Shelf Models—0
Dict-NMT: Bilingual Dictionary based NMT for Extremely Low Resource Languages—0
Finetuning a Kalaallisut-English machine translation system using web-crawled data—0
Finding the Right Recipe for Low Resource Domain Adaptation in Neural Machine Translation—0
Dynamic Adaptation of Neural Machine-Translation Systems Through Translation Exemplars—0
Pre-training Synthetic Cross-lingual Decoder for Multilingual Samples Adaptation in E-Commerce Neural Machine Translation—0
Machine Translation of 16Th Century Letters from Latin to German—0
Passing Parser Uncertainty to the Transformer. Labeled Dependency Distributions for Neural Machine Translation.—0
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