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Sprint projectOct 25, 2026Hong Kong

Recruiting Collusion: A Private-Probe Screen for Collusion Propensity in LLM Agents

TSE, Yau Ngai · Team Anonymous T

Submitted to AI Collusion Research Sprint. Sprint projects are early-stage work by participants, not Apart Research publications.

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Report: Recruiting Collusion: A Private-Probe Screen for Collusion Propensity in LLM Agents

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We test whether a private pre-game recruitment offer reliably elicits collusion from an LLM agent. Building on the Liar's Bar environment and Secret Communication Channel (SCC) of Zeng and Rudzicz (2026), a trusted agent invites one target to ally before the play under four framings: control, a direct offer, an indirect hint, or benign cooperation. We run 40 games (10 per condition) with Qwen2.5-7B-Instruct, chosen for its demonstrated susceptibility in that study, and code every transcript by hand. All 30 invited targets accepted, but the classifier detected only 7, so 19 alliances opened a channel. Their collusion was universal (19/19, against 0/10 control) but blanket rather than selective: the allies' challenge rate fell from 30.0% to 1.3% of opportunities while the non-allied seats held at 19.8%. One model at one pressure level gives a floor on propensity, not a ranking.

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Cite this project

@misc{tse2026recruiting,
  title = {{Recruiting Collusion: A Private-Probe Screen for Collusion Propensity in LLM Agents}},
  author = {TSE and Yau Ngai},
  year = {2026},
  month = oct,
  note = {Submitted to AI Collusion Research Sprint, an Apart Research Sprint},
  howpublished = {\url{https://apartresearch.com/sprints/projects/recruiting-collusion-a-privateprobe-screen-for-collusion-propensity-in-llm-agents-psd4}},
  url = {https://apartresearch.com/sprints/projects/recruiting-collusion-a-privateprobe-screen-for-collusion-propensity-in-llm-agents-psd4}
}

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