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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 676–700 of 1773 papers

TitleStatusHype
Continual Mixed-Language Pre-Training for Extremely Low-Resource Neural Machine TranslationCode0
Boosting Neural Machine Translation from Finnish to Northern Sámi with Rule-Based Backtranslation—0
Hidden Backdoors in Human-Centric Language ModelsCode1
Generating Lead Sheets with Affect: A Novel Conditional seq2seq FrameworkCode1
Shellcode_IA32: A Dataset for Automatic Shellcode GenerationCode1
Addressing the Vulnerability of NMT in Input PerturbationsCode0
Zero-shot Cross-lingual Transfer of Neural Machine Translation with Multilingual Pretrained EncodersCode0
From Fully Trained to Fully Random Embeddings: Improving Neural Machine Translation with Compact Word Embedding Tables—0
Sentence Alignment with Parallel Documents Facilitates Biomedical Machine TranslationCode0
Sentence Concatenation Approach to Data Augmentation for Neural Machine Translation—0
Context-Adaptive Document-Level Neural Machine Translation—0
Investigating Failures of Automatic Translation in the Case of Unambiguous Gender—0
Simultaneous Multi-Pivot Neural Machine Translation—0
Reward Optimization for Neural Machine Translation with Learned MetricsCode1
First the worst: Finding better gender translations during beam searchCode0
Sometimes We Want Translationese—0
Domain Adaptation and Multi-Domain Adaptation for Neural Machine Translation: A Survey—0
The Curious Case of Hallucinations in Neural Machine TranslationCode0
Source and Target Bidirectional Knowledge Distillation for End-to-end Speech Translation—0
Samanantar: The Largest Publicly Available Parallel Corpora Collection for 11 Indic LanguagesCode1
Sentiment-based Candidate Selection for NMTCode0
A Sketch-Based Neural Model for Generating Commit Messages from DiffsCode1
Better Neural Machine Translation by Extracting Linguistic Information from BERTCode0
Attention Forcing for Machine TranslationCode0
Efficient Unsupervised NMT for Related Languages with Cross-Lingual Language Models and Fidelity Objectives—0
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