Actionable Guidance for High-Consequence AI Risk Management: Towards Standards Addressing AI Catastrophic Risks

17 June 2022

Papers citing "Actionable Guidance for High-Consequence AI Risk Management: Towards Standards Addressing AI Catastrophic Risks"

5 / 5 papers shown

Title
GUARD-D-LLM: An LLM-Based Risk Assessment Engine for the Downstream uses of LLMs Sundaraparipurnan Narayanan Sandeep Vishwakarma 34 3 0 02 Apr 2024
Open-Sourcing Highly Capable Foundation Models: An evaluation of risks, benefits, and alternative methods for pursuing open-source objectives Elizabeth Seger Noemi Dreksler Richard Moulange Emily Dardaman Jonas Schuett ... Emma Bluemke Michael Aird Patrick Levermore Julian Hazell Abhishek Gupta 11 40 0 29 Sep 2023
Can LLM-Generated Misinformation Be Detected? Canyu Chen Kai Shu DeLMO 31 158 0 25 Sep 2023
Both eyes open: Vigilant Incentives help Regulatory Markets improve AI Safety Paolo Bova A. D. Stefano H. Anh 18 4 0 06 Mar 2023
Training language models to follow instructions with human feedback Long Ouyang Jeff Wu Xu Jiang Diogo Almeida Carroll L. Wainwright ... Amanda Askell Peter Welinder Paul Christiano Jan Leike Ryan J. Lowe OSLM ALM 311 11,915 0 04 Mar 2022