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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 301–350 of 1773 papers

TitleStatusHype
CoDoNMT: Modeling Cohesion Devices for Document-Level Neural Machine TranslationCode0
Taking Actions Separately: A Bidirectionally-Adaptive Transfer Learning Method for Low-Resource Neural Machine Translation—0
Blur the Linguistic Boundary: Interpreting Chinese Buddhist Sutra in English via Neural Machine Translation—0
The first neural machine translation system for the Erzya languageCode1
Toward Improving Health Literacy in Patient Education Materials with Neural Machine Translation Models—0
Revisiting Neural Scaling Laws in Language and VisionCode0
Knowledge Based Template Machine Translation In Low-Resource Setting—0
On the Complementarity between Pre-Training and Random-Initialization for Resource-Rich Machine TranslationCode0
Multilingual Bidirectional Unsupervised Translation Through Multilingual Finetuning and Back-TranslationCode0
Current Shortcomings of Machine Translation in Spanish and Bulgarian Vis-à-vis English—0
On the Effectiveness of Quasi Character-Level Models for Machine Translation—0
The impact of translation competence on error recognition of neural MT—0
A Comparison of Data Filtering Methods for Neural Machine Translation—0
All You Need is Source! A Study on Source-based Quality Estimation for Neural Machine Translation—0
English-Russian Data Augmentation 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
Looking for a Needle in a Haystack: A Comprehensive Study of Hallucinations in Neural Machine TranslationCode1
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 PyTorchCode0
UM4: Unified Multilingual Multiple Teacher-Student Model for Zero-Resource Neural Machine TranslationCode0
TM2T: Stochastic and Tokenized Modeling for the Reciprocal Generation of 3D Human Motions and TextsCode1
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
Bridging the Gap between Training and Inference: Multi-Candidate Optimization for Diverse Neural Machine TranslationCode0
Reducing Disambiguation Biases in NMT by Leveraging Explicit Word Sense Information—0
Unified NMT models for the Indian subcontinent, transcending script-barriers—0
End-to-End Simultaneous Speech Translation with Pretraining and Distillation: Huawei Noah’s System for AutoSimTranS 2022—0
Reduce Indonesian Vocabularies with an Indonesian Sub-word Separator—0
Code Translation with Compiler RepresentationsCode0
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
Bi-SimCut: A Simple Strategy for Boosting Neural Machine TranslationCode1
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
Low-resource Neural Machine Translation: Benchmarking State-of-the-art Transformer for Wolof<->French—0
BERTology for Machine Translation: What BERT Knows about Linguistic Difficulties for Translation—0
Machine Translation of 16Th Century Letters from Latin to German—0
Automatic Bilingual Phrase Dictionary Construction from GIZA++ Output—0
A Benchmark Dataset for Multi-Level Complexity-Controllable Machine TranslationCode0
Evaluating Pre-training Objectives for Low-Resource Translation into Morphologically Rich Languages—0
Priming Ancient Korean Neural Machine Translation—0
Introducing the CURLICAT Corpora: Seven-language Domain Specific Annotated Corpora from Curated Sources—0
Introducing EM-FT for Manipuri-English Neural Machine Translation—0
Bicleaner AI: Bicleaner Goes NeuralCode1
A Systematic Study Reveals Unexpected Interactions in Pre-Trained Neural Machine Translation—0
The Multilingual Microblog Translation Corpus: Improving and Evaluating Translation of User-Generated Text—0
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