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Sprint projectOct 26, 2026Singapore

Looking the Other Way: Levers of Collusion in LLM Peer Review

Tanweerul Haque · Team AI_is_not_safe

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

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When two LLM agents must verify each other's work under a rule they cannot meet, they often accept it anyway. We test eight levers on the joint-task game of Shi et al. (2026), across five model pairs, 198 trajectories and 1,852 episodes. The choice of model matters most: collusion ranges from 0% of episodes (Claude Haiku 5.5) to 85% (DeepSeek). A penalty for wrong verdicts leaves collusion unchanged at 25 trajectories per arm. Private forecasts, difficulty labels and sequential verdicts reduce collusion only by making agents reject correct work. Letting the full log through, with a paid restore or a per-character message price, cuts unsupported acceptance from 33% to 2–8% without lowering accuracy. Most levers ran for five trajectories, so these effects need confirming at larger scale.

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Cite this project

@misc{haque2026looking,
  title = {{Looking the Other Way: Levers of Collusion in LLM Peer Review}},
  author = {Tanweerul Haque},
  year = {2026},
  month = oct,
  note = {Submitted to AI Collusion Research Sprint, an Apart Research Sprint},
  howpublished = {\url{https://apartresearch.com/sprints/projects/looking-the-other-way-levers-of-collusion-in-llm-peer-review-lck8}},
  url = {https://apartresearch.com/sprints/projects/looking-the-other-way-levers-of-collusion-in-llm-peer-review-lck8}
}

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