1 citations · 1 across the 3 of their papers we have counts for
4 papers
BashArena: A Control Setting for Highly Privileged AI Agents
Adam Kaufman, James Lucassen, Tyler Tracy +2
Future AI agents might run autonomously with elevated privileges. If these agents are misaligned, they might abuse these privileges to cause serious damage. The field of AI control…
Combining Cost-Constrained Runtime Monitors for AI Safety
Tim Tian Hua, James Baskerville, Henri Lemoine +3
Monitoring AIs at runtime can help us detect and stop harmful actions. In this paper, we study how to efficiently combine multiple runtime monitors into a single monitoring protoco…
Ctrl-Z: Controlling AI Agents via Resampling
Aryan Bhatt, Cody Rushing, Adam Kaufman +5
Control evaluations measure whether monitoring and security protocols for AI systems prevent intentionally subversive AI models from causing harm. Our work presents the first contr…
Adaptive Deployment of Untrusted LLMs Reduces Distributed Threats
Jiaxin Wen, Vivek Hebbar, Caleb Larson +9
As large language models (LLMs) become increasingly capable, it is prudent to assess whether safety measures remain effective even if LLMs intentionally try to bypass them. Previou…