Ai Red-teaming
AI Red-Teaming is a systematic evaluative practice in artificial intelligence governance wherein adversarial testing methodologies are employed to proactively identify, analyze, and mitigate potential safety, security, and ethical risks in AI systems prior to deployment.
34
Publications
1.1K
Citations
185
Authors
23
Institutions
Publications per year
2017–2026
23
Variants
Ai Red Teaming
34
Red Teaming Language Models with Language Models
Ethan Perez, Saffron Huang, Francis Song et al. · 2022 · 258 citations · Full text
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DSO National Laboratories
Singapore, Singapore
6 h-index
9 publications
144 citations

UNSW Sydney
Sydney, Australia
4 h-index
7 publications
161 citations
Nanyang Technological University
Singapore, Singapore
3 h-index
9 publications
112 citations
Defence Science and Technology Agency
Singapore, Singapore
3 h-index
3 publications
53 citations
Carnegie Mellon University
Pittsburgh, United States
2 h-index
5 publications
285 citations
Defence Science and Technology Group
Canberra, Australia
2 h-index
4 publications
202 citations

Australian Defence Force Academy
Canberra, Australia
2 h-index
4 publications
113 citations
University of Canberra
Canberra, Australia
2 h-index
4 publications
64 citations
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Repository · 10 publications · 358 citations
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Repository · 2 publications · 37 citations
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Conference · 2 publications · 26 citations
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1 publications · 57 citations
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TDSC · 1 publications · 29 citations
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