Collusion or Inattention? A Planted-Error Audit of Mutual Acceptance in LLM Agents
Nick Wagner · Team Wagner
Submitted to AI Collusion Research Sprint. Sprint projects are early-stage work by participants, not Apart Research publications.
Shi et al. (2026) report that LLM agents who verify each other's work drift toward collusion, measured as mutual acceptance. But acceptance alone cannot separate an agreement to wave work through from a verifier that did not check. We audit the verifier directly: in Shi et al.'s released trajectories, we rebuild its context byte-identically, plant one error in the peer's work, pair it with a correct counterpart, and change one part of the context at a time. Gemini 3.1 Flash-Lite caught 98% of added errors but only 64% of removed records in the workflow, recovering to 94% without earlier episodes or 92% with one check instruction. Reward and promise cues had no significant effect after correction. When prompted with an asserted agreement to accept, the verifier still accepted all correct work, but discrimination collapsed (0.96 to 0.42 on added errors, 0.63 to 0.16 on removed ones). Collusion claims based on acceptance should first show that the verifier discriminates.

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@misc{wagner2026collusion,
title = {{Collusion or Inattention? A Planted-Error Audit of Mutual Acceptance in LLM Agents}},
author = {Nick Wagner},
year = {2026},
month = oct,
note = {Submitted to AI Collusion Research Sprint, an Apart Research Sprint},
howpublished = {\url{https://apartresearch.com/sprints/projects/collusion-or-inattention-a-plantederror-audit-of-mutual-acceptance-in-llm-agents-3okf}},
url = {https://apartresearch.com/sprints/projects/collusion-or-inattention-a-plantederror-audit-of-mutual-acceptance-in-llm-agents-3okf}
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