Machine Translation
Fast Sampling via Discrete Non-Markov Diffusion Models with Predetermined Transition Time
Diffusion-based generative models, as first introduced by Sohl-Dickstein et al. (2015), have shown
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- North America > United States > California > Los Angeles County > Los Angeles (0.28)
- Asia > Middle East > Oman (0.04)
- North America > United States > Maryland > Baltimore (0.04)
- Europe > Germany > Berlin (0.04)
Genre:
- Research Report > Experimental Study (0.92)
- Research Report > New Finding (0.67)
Technology:
- Information Technology > Artificial Intelligence > Machine Learning > Neural Networks (1.00)
- Information Technology > Artificial Intelligence > Natural Language > Machine Translation (0.68)
- Information Technology > Artificial Intelligence > Representation & Reasoning > Uncertainty > Bayesian Inference (0.45)
- Information Technology > Artificial Intelligence > Machine Learning > Learning Graphical Models > Directed Networks > Bayesian Learning (0.45)
Technology:
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- Asia > Middle East > Iran > Tehran Province > Tehran (0.04)
- North America > United States > Iowa > Story County > Ames (0.04)
- North America > United States > California > Santa Clara County > San Jose (0.04)
- North America > United States > California > Santa Clara County > Mountain View (0.04)
Genre:
- Research Report > Experimental Study (0.93)
- Research Report > New Finding (0.67)
Technology:
- Information Technology > Software > Programming Languages (1.00)
- Information Technology > Artificial Intelligence > Representation & Reasoning (1.00)
- Information Technology > Artificial Intelligence > Natural Language > Machine Translation (1.00)
- (3 more...)
DASpeech: Directed Acyclic Transformer for Fast and High-quality Speech-to-Speech Translation Qingkai Fang 1,2, Y an Zhou 1,2, Y ang Feng 1,2 1
In this paper, we propose DASpeech, a non-autoregressive direct S2ST model which realizes both fast and high-quality S2ST.
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- Europe > Austria > Vienna (0.14)
- Asia > South Korea > Incheon > Incheon (0.04)
- North America > Canada > British Columbia > Vancouver (0.04)
- (12 more...)
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- Information Technology > Artificial Intelligence > Speech > Speech Recognition (1.00)
- Information Technology > Artificial Intelligence > Representation & Reasoning (1.00)
- Information Technology > Artificial Intelligence > Natural Language > Machine Translation (1.00)
- Information Technology > Artificial Intelligence > Machine Learning > Neural Networks (0.93)
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- North America > United States (0.04)
- South America > Chile > Santiago Metropolitan Region > Santiago Province > Santiago (0.04)
- Asia > South Korea > Incheon > Incheon (0.04)
- Asia > Middle East > Jordan (0.04)
Technology:
- Information Technology > Artificial Intelligence > Natural Language > Machine Translation (1.00)
- Information Technology > Artificial Intelligence > Speech > Speech Recognition (0.95)
- Information Technology > Artificial Intelligence > Machine Learning > Neural Networks > Deep Learning (0.94)
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- Europe > Poland (0.04)
- Europe > Netherlands > North Holland > Amsterdam (0.04)
Technology:
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- Africa > Ghana (0.05)
- North America > United States > Pennsylvania > Lackawanna County > Scranton (0.04)
- Asia > China > Jiangsu Province > Nanjing (0.04)
- Europe > United Kingdom (0.04)
Industry:
- Leisure & Entertainment (0.68)
- Health & Medicine (0.68)
- Government > Regional Government > North America Government > United States Government (0.47)
- Media > Music (0.46)
Technology:
- Information Technology > Artificial Intelligence > Natural Language > Machine Translation (0.94)
- Information Technology > Artificial Intelligence > Machine Learning > Neural Networks > Deep Learning (0.51)
Country:
- North America > United States > Minnesota > Hennepin County > Minneapolis (0.14)
- North America > United States > Washington > King County > Seattle (0.04)
- North America > United States > Massachusetts > Middlesex County > Cambridge (0.04)
- (8 more...)
Technology:
A Appendix
The complete list may be seen in Table 8. Here are a few general notes about these strings: 1. Based on their recommendations, we did the following: 1. zh, zh_Latn: This resulted in the special filters described below. URLs) the corpora were in languages different from the LangID predictions. This is mainly mis-rendered PDFs and may have practical applications for denoising, or for decoding such garbled PDFs.
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- Oceania > Tonga (0.04)
- North America > United States (0.04)
- South America > Peru > Huánuco Department > Huánuco Province > Huánuco (0.04)
- (24 more...)
Technology:
- Information Technology > Artificial Intelligence > Machine Learning (1.00)
- Information Technology > Communications > Social Media (0.67)
- Information Technology > Artificial Intelligence > Natural Language > Machine Translation (0.46)
A Multilingual And Document Level Large Audited
We then train and release a 10.7B-parameter
Technology:
- Information Technology > Artificial Intelligence > Natural Language > Machine Translation (1.00)
- Information Technology > Artificial Intelligence > Machine Learning > Neural Networks > Deep Learning (0.67)