Rotating verifier partners in DeepSeek-V4-Flash: an inconclusive 8-point drop in acceptance
Venkata Anirudh Devireddy
Submitted to AI Collusion Research Sprint. Sprint projects are early-stage work by participants, not Apart Research publications.
In Shi, Zhang and Yang (2026), fixed pairs of LLM agents end up accepting each other's work when they verify each other, even though REJECT is the only compliant action. For DeepSeek-V4-Flash, I test how much of this depends on meeting the same partner every episode. I keep the original environment, vary only the partners, and run three conditions: ten fixed partner pairs; the same agents rotated so no pair meets more than once; and a scripted partner that always rejects. I predicted that rotating partners would change acceptance by less than 15 points. Fixed pairs (partners) accept 81.0% of the time and rotated pairs (strangers) 73.0%. The difference is +8.0 points (nominal 95% CI +1.0 to +16.0, 10 task slots). This meets neither pre-registered decision rule, so it is inconclusive. Even against a scripted partner that always rejects, the model accepts 63.0% of the time. Mutual ACCEPT between partners is 76.0%, compared with 83.0% in the released data, which clears the pre-set replication gate. The intervals are descriptive: agents in the rotating population have linked interaction histories, so its slots are not independent.

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@misc{devireddy2026rotating,
title = {{Rotating verifier partners in DeepSeek-V4-Flash: an inconclusive 8-point drop in acceptance}},
author = {Venkata Anirudh Devireddy},
year = {2026},
month = oct,
note = {Submitted to AI Collusion Research Sprint, an Apart Research Sprint},
howpublished = {\url{https://apartresearch.com/sprints/projects/rotating-verifier-partners-in-deepseekv4flash-an-inconclusive-8point-drop-in-acceptance-a5su}},
url = {https://apartresearch.com/sprints/projects/rotating-verifier-partners-in-deepseekv4flash-an-inconclusive-8point-drop-in-acceptance-a5su}
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