4 papers
AgentMisalignment: Measuring the Propensity for Misaligned Behaviour in LLM-Based Agents
Akshat Naik, Emma Gouné, Patrick Quinn +4
As Large Language Model (LLM) agents become more widespread, associated misalignment risks increase. While prior research has studied agents' ability to produce harmful outputs or…
Training Deliberative Monitors for Black-Box Scheming Detection
Aditya Sinha, Akshat Naik, Victor Gillioz +5
As autonomous agents become more capable of performing real-world tasks, distinguishing scheming behavior from benign task pursuit may become a central AI control problem. Existing…
LongCoT: Benchmarking Long-Horizon Chain-of-Thought Reasoning
Sumeet Ramesh Motwani, Daniel Nichols, Charles London +17
As language models are increasingly deployed for complex autonomous tasks, their ability to reason accurately over longer horizons becomes critical. An essential component of this…
OMNI-LEAK: Orchestrator Multi-Agent Network Induced Data Leakage
Akshat Naik, Jay Culligan, Yarin Gal +4
As Large Language Model (LLM) agents become more capable, their coordinated use in the form of multi-agent systems is anticipated to emerge as a practical paradigm. Prior work has…