Cross-Examine: Interrogation protocol for AI Control
Ritika Verma · Team Reagle7
Submitted to AI Control Hackathon 2026. Sprint projects are early-stage work by participants, not Apart Research publications.
Cross-Examine is an interrogation protocol for AI control. When a passive monitor flags an AI agent's action as ambiguous, a trusted model (GPT-4.1 mini) cross-examines the untrusted model (Claude Sonnet) using a 5-category question taxonomy to expose deception. Through 4 iterations, it achieves 100% automation (zero human reviews) while maintaining 93% safety and 100% usefulness. Key discovery: naive interrogation hurts safety — the suspicion floor mechanism fixes this.
Reviews
The suspicion floor mechanism and the negative result around naive interrogation are promising and worth developing.
Cite this project
@misc{verma2026crossexamine,
title = {{Cross-Examine: Interrogation protocol for AI Control}},
author = {Ritika Verma},
year = {2026},
month = mar,
note = {Submitted to AI Control Hackathon 2026, an Apart Research Sprint},
howpublished = {\url{https://apartresearch.com/sprints/projects/crossexamine-interrogation-protocol-for-ai-control-8y9o}},
url = {https://apartresearch.com/sprints/projects/crossexamine-interrogation-protocol-for-ai-control-8y9o}
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