Detecting multi-agent collusion via multi-agent interpretability
In brief
- HELIOS uses activation probes to detect non-verbal collusion among AI agents.
- Methods achieve 0.99 to 1.00 AUROC on steganographic collusion tasks.
- Results show partial transferability to environments with emergent collusion.
This paper introduces HELIOS, a framework leveraging joint inference statistics and activation probes to detect collusion among AI agents. Evaluated on the NARCBench benchmark, the methods achieve near-perfect AUROC (0.99-1.00) in detecting non-verbal collusion, even when transferred to unseen environments.
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