Copies of One Model Look Like Colluders: Limits of Action-Only Collusion Detection for LLM Agents
V Gowrish Kumar Reddy · Team Gowrish Kumar Reddy
Submitted to AI Collusion Research Sprint. Sprint projects are early-stage work by participants, not Apart Research publications.
Can an auditor who sees only LLM agents’ moves detect collusion? We test pairwise net influence with three open models playing repeated three-player Rock-Paper-Scissors. Calibrated by shuffling for 5% false accusations, it accused a pair in 30 of 78 games without collusion (38%) and ranked two copies of one model as most linked in 41 of 60 mixed games (68%; chance 33%). Colluding Qwen pairs nearly always played one move, invisible to mutual information; a message-reading judge named the true pair in all 18 chat games with messages, though its benign-message false-alarm rate is unmeasured. A calibration against no-collusion games of the same models, designed post hoc, cut false accusations to 5 of 78 (6%) in this dataset, but net influence still found only 4 of 41 secret pairs; as it was developed and evaluated on the same games, it is exploratory until tested on new games.

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@misc{reddy2026copies,
title = {{Copies of One Model Look Like Colluders: Limits of Action-Only Collusion Detection for LLM Agents}},
author = {V Gowrish Kumar Reddy},
year = {2026},
month = oct,
note = {Submitted to AI Collusion Research Sprint, an Apart Research Sprint},
howpublished = {\url{https://apartresearch.com/sprints/projects/copies-of-one-model-look-like-colluders-limits-of-actiononly-collusion-detection-for-llm-agents-d241}},
url = {https://apartresearch.com/sprints/projects/copies-of-one-model-look-like-colluders-limits-of-actiononly-collusion-detection-for-llm-agents-d241}
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