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Cited by 175

The DOI matches its Crossref record; 47 of the 47 references it cites were found in a registry or an index.

Information Leakage in Embedding Models

Song, Congzheng, Raghunathan, Ananth·2020·Proceedings of the 2020 ACM SIGSAC Conference on Computer and Communications Security
DOI 10.1145/3372297.3417270
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Abstract

Embeddings are functions that map raw input data to low-dimensional vector representations, while preserving important semantic information about the inputs. Pre-training embeddings on a large amount of unlabeled data and fine-tuning them for downstream tasks is now a de facto standard in achieving state of the art learning in many domains.

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Citations

Cites

Research works printed but not linked: 35

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Metadata

Authors
Song, C., & Raghunathan, A.
Affiliations
  • Cornell University & Google Brain, New York, NY, USA
  • Facebook & Google Brain, Melon Park, CA, USA
Venue
Proceedings of the 2020 ACM SIGSAC Conference on Computer and Communications Security
Publisher
ACM
Published
2020-10-30
Pages
377-390
DOI
10.1145/3372297.3417270
Cited by
175
References
47
Licence
www.acm.org/publications/policies/copyright_policy#Background (vor)

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