Initial Thoughts on Cybersecurity and Reproducibility
IEEE International Symposium on High-Performance Parallel Distributed Computing (HPDC)(2019)CCF B
Informat Sci Inst | Univ Illinois | Univ Tennessee | Indiana Univ
Abstract
Cybersecurity, which serves to protect computer systems and data from malicious and accidental abuse and changes, both supports and challenges the reproducibility of computational science. This position paper explores a research agenda by enumerating a set of two types of challenges that emerge at the intersection of cybersecurity and reproducibility: challenges that cybersecurity has in supporting the reproducibility of computational science, and challenges cybersecurity creates for reproducibility of computational science.
MoreTranslated text
Key words
computer security,computational science reproducibility,data integrity
PDF
View via Publisher
AI Read Science
AI Summary
AI Summary is the key point extracted automatically understanding the full text of the paper, including the background, methods, results, conclusions, icons and other key content, so that you can get the outline of the paper at a glance.
Example
Background
Key content
Introduction
Methods
Results
Related work
Fund
Key content
- Pretraining has recently greatly promoted the development of natural language processing (NLP)
- We show that M6 outperforms the baselines in multimodal downstream tasks, and the large M6 with 10 parameters can reach a better performance
- We propose a method called M6 that is able to process information of multiple modalities and perform both single-modal and cross-modal understanding and generation
- The model is scaled to large model with 10 billion parameters with sophisticated deployment, and the 10 -parameter M6-large is the largest pretrained model in Chinese
- Experimental results show that our proposed M6 outperforms the baseline in a number of downstream tasks concerning both single modality and multiple modalities We will continue the pretraining of extremely large models by increasing data to explore the limit of its performance
Try using models to generate summary,it takes about 60s
Must-Reading Tree
Example

Generate MRT to find the research sequence of this paper
Related Papers
Xanthus: Push-button Orchestration of Host Provenance Data Collection.
PROCEEDINGS OF THE 3RD INTERNATIONAL WORKSHOP ON PRACTICAL REPRODUCIBLE EVALUATION OF COMPUTER SYSTEMS, P-RECS 2020 2020
被引用4
Data Disclaimer
The page data are from open Internet sources, cooperative publishers and automatic analysis results through AI technology. We do not make any commitments and guarantees for the validity, accuracy, correctness, reliability, completeness and timeliness of the page data. If you have any questions, please contact us by email: report@aminer.cn
Chat Paper
去 AI 文献库 对话