11 citations · 18 across the 10 of their papers we have counts for
4 papers · 1 filter
GDM AI Control Roadmap
Mary Phuong, Erik Jenner, Laurent Simon +4
AI agents are rapidly accelerating work at frontier AI companies, helping with AI R&D, cyber-defence, and advancing scientific discoveries. As these agents become more tightly inte…
Realistic honeypot evaluations for scheming propensity
Victoria Krakovna, David Lindner, Lewis Ho +2
We introduce scheming honeypot evaluations, a framework for testing whether models will pursue instrumental goals if given the opportunity. Our scheming honeypot evaluations take t…
Gram: Assessing sabotage propensities via automated alignment auditing
David Lindner, Victoria Krakovna, Sebastian Farquhar
We introduce Gram, an automated alignment auditing framework to assess the propensity of AI agents to engage in sabotage. We evaluate Gemini models across 17 simulated agentic depl…
Latent Instruction Representation Alignment: defending against jailbreaks, backdoors and undesired knowledge in LLMs
Eric Easley, Sebastian Farquhar
We address jailbreaks, backdoors, and unlearning for large language models (LLMs). Unlike prior work, which trains LLMs based on their actions when given malign instructions, our m…