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1 Ergebnisse
1
An Empirical Study of Artifacts and Security Risks in the P..:
, In:
Proceedings of the 2022 ACM Workshop on Software Supply Chain Offensive Research and Ecosystem Defenses
,
Jiang, Wenxin
;
Synovic, Nicholas
;
Sethi, Rohan
... - p. 105-114 , 2022
Link:
https://dl.acm.org/doi/10.1145/3560835.3564547
RT T1 <cTitle>Proceedings of the 2022 ACM Workshop on Software Supply Chain Offensive Research and Ecosystem Defenses</cTitle>: T1 <Title>An Empirical Study of Artifacts and Security Risks in the Pre-trained Model Supply Chain</Title> UL https://suche.suub.uni-bremen.de/peid=acm-3564547&Exemplar=1&LAN=DE A1 Jiang, Wenxin A1 Synovic, Nicholas A1 Sethi, Rohan A1 Indarapu, Aryan A1 Hyatt, Matt A1 Schorlemmer, Taylor R. A1 Thiruvathukal, George K. A1 Davis, James C. PB ACM YR 2022 K1 deep neural networks K1 empirical software engineering K1 machine learning K1 model hubs K1 software reuse K1 software supply chain K1 General and reference K1 Cross-computing tools and techniques K1 Empirical studies K1 Computing methodologies K1 Machine learning SP 105 OP 114 LK http://dx.doi.org/https://dl.acm.org/doi/10.1145/3560835.3564547 DO https://dl.acm.org/doi/10.1145/3560835.3564547 SF ELIB - SuUB Bremen
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