collaborators

5 papers

cs.AI2026

"Did you lie?" Evaluating Lie Detectors across Model Scale and Belief-Verified Model Organisms

Alan Cooney, David Africa, Geoffrey Irving

Robust lie detectors for language models could enable powerful techniques for auditing, monitoring, and post-hoc investigation of model behaviour, but evaluating them requires test…

cs.AI2026

Behavioural Analysis of Alignment Faking

Nathaniel Mitrani Hadida, Rhea Karty, David Williams-King +1

Alignment faking (AF) refers to a model strategically complying with a training objective to avoid behavioural modification while preserving its deployment preferences. Understandi…

cs.CR2025

Practical challenges of control monitoring in frontier AI deployments

David Lindner, Charlie Griffin, Tomek Korbak +4

Automated control monitors could play an important role in overseeing highly capable AI agents that we do not fully trust. Prior work has explored control monitoring in simplified…

cs.LG2025

Async Control: Stress-testing Asynchronous Control Measures for LLM Agents

Asa Cooper Stickland, Jan Michelfeit, Arathi Mani +6

LLM-based software engineering agents are increasingly used in real-world development tasks, often with access to sensitive data or security-critical codebases. Such agents could i…

cs.CR2025

RepliBench: Evaluating the Autonomous Replication Capabilities of Language Model Agents

Sid Black, Asa Cooper Stickland, Jake Pencharz +7

Uncontrollable autonomous replication of language model agents poses a critical safety risk. To better understand this risk, we introduce RepliBench, a suite of evaluations designe…