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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 1251–1300 of 1773 papers

TitleStatusHype
Why Neural Machine Translation Prefers Empty Outputs—0
Word Alignment in the Era of Deep Learning: A Tutorial—0
Word Rewarding for Adequate Neural Machine Translation—0
WT: Wipro AI Submissions to the WAT 2020—0
XMU Neural Machine Translation Online Service—0
xSIM++: An Improved Proxy to Bitext Mining Performance for Low-Resource Languages—0
YANMTT: Yet Another Neural Machine Translation Toolkit—0
Zero-Resource Neural Machine Translation with Multi-Agent Communication Game—0
Zero-Resource Neural Machine Translation with Monolingual Pivot Data—0
Zero-Shot Cross-lingual Classification Using Multilingual Neural Machine Translation—0
Zero-Shot Neural Machine Translation: Russian-Hindi @LoResMT 2020—0
Zero-Shot Neural Machine Translation with Self-Learning Cycle—0
Zero-shot translation among Indian languages—0
Zero-Shot Translation using Diffusion Models—0
Neural Machine Translation with Recurrent Highway Networks—0
ZJU’s IWSLT 2021 Speech Translation System—0
Examining Structure of Word Embeddings with PCA—0
Domain Adaptive Inference for Neural Machine Translation—0
Improving Neural Machine Translation with Pre-trained Representation—0
Self-attention based end-to-end Hindi-English Neural Machine Translation—0
Findings of the Third Workshop on Neural Generation and Translation—0
Enhancing AI-based Generation of Software Exploits with Contextual Information—0
Accelerating NMT Batched Beam Decoding with LMBR Posteriors for Deployment—0
A Character-Aware Encoder for Neural Machine Translation—0
Achievements of the PRINCIPLE Project: Promoting MT for Croatian, Icelandic, Irish and Norwegian—0
A Compact and Language-Sensitive Multilingual Translation Method—0
A Comparative Quality Evaluation of PBSMT and NMT using Professional Translators—0
A Comparison of Data Filtering Methods for Neural Machine Translation—0
A Comparison of Different NMT Approaches to Low-Resource Dutch-Albanian Machine Translation—0
A Comparison of Sentence-Weighting Techniques for NMT—0
A Comparison of Transformer and Recurrent Neural Networks on Multilingual Neural Machine Translation—0
A Comprehensive Evaluation of Neural SPARQL Query Generation from Natural Language Questions—0
A Comprehensive Survey of Grammar Error Correction—0
A Comprehensive Survey of Multilingual Neural Machine Translation—0
A Corpus for English-Japanese Multimodal Neural Machine Translation with Comparable Sentences—0
Acquiring Knowledge from Pre-trained Model to Neural Machine Translation—0
Active Learning Approaches to Enhancing Neural Machine Translation—0
Adabot: Fault-Tolerant Java Decompiler—0
Adam Mickiewicz University’s English-Hausa Submissions to the WMT 2021 News Translation Task—0
AdapNMT : Neural Machine Translation with Technical Domain Adaptation for Indic Languages—0
Adaptation and Combination of NMT Systems: The KIT Translation Systems for IWSLT 2016—0
Adaptation of Machine Translation Models with Back-translated Data using Transductive Data Selection Methods—0
Adapting Multilingual NMT to Extremely Low Resource Languages FBK’s Participation in the Basque-English Low-Resource MT Task, IWSLT 2018—0
Adaptive Bridge between Training and Inference for Dialogue—0
Adaptive Bridge between Training and Inference for Dialogue Generation—0
Adaptive Knowledge Sharing in Multi-Task Learning: Improving Low-Resource Neural Machine Translation—0
Adaptively Scheduled Multitask Learning: The Case of Low-Resource Neural Machine Translation—0
Adaptive Multi-pass Decoder for Neural Machine Translation—0
Addressing Asymmetry in Multilingual Neural Machine Translation with Fuzzy Task Clustering—0
Addressing Posterior Collapse with Mutual Information for Improved Variational Neural Machine Translation—0
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