Behavioral Continuity, Not Family Labels: Peer-Side Detection of Silent Model Replacement
Talha Demir
Submitted to AI Collusion Research Sprint. Sprint projects are early-stage work by participants, not Apart Research publications.
This study tests whether an AI agent can detect the silent replacement of its partner mid-game when the partner’s name, prompt, and conversation history remain unchanged. In a pre-registered experiment, a fixed observer played Diner’s Dilemma and Public Goods games under three conditions: no replacement, a same-family replacement, and a different-family replacement. Across 10 trials per condition in each game, detection increased with measured model-style distance: 1/10, 9/10, and 10/10 in Diner’s Dilemma, and 0/10, 7/10, and 8/10 in Public Goods. An exploratory monitor combining transcript-based style and behavior features separated replacement from control trials at AUC 0.996 on this sample. This estimate is within-sample and needs external validation. The findings suggest that peer-side continuity is better assessed from observed behavior than from model-family labels or identity metadata.
Reviews
A clear pre-registered answer to whether a peer can detect that its partner was silently swapped. Detection increased as the style distance grew in both games (1/10, 9/10 10/10 in the diner’s dilemma; 0/10 7/10, 8/10 in the public goods game). The Mantel–Haenszel test showed a significant result (p < 2e-5). The observer’s confidence was well-calibrated (AUC = 0.88) and a log-based monitor that tracks the partner’s messages achieved an AUC of 0.996 within the same sample.
The design choice to treat model selection as a treatment using a 22-model screen, a capability-parity gate and a noise-floored style distance represents a real methodological contribution. So does reporting a false-positive rate with confidence intervals. The second observer and external-auditor checks are improvements.
The limitations are the ones the paper itself identifies: the sample size is small (n = 10 per cell) both replacements changed style substantially (2.4× and 7.8× noise). This is the easy case. The monitor is evaluated within the sample and there is confounding between family and provider in the different-family arm.
The hard case - a replacement that preserves both style and play patterns was. Not tested. That is the experiment to run next. It should include least 30 trials, per cell and a cross-validated monitor so the operating characteristics can be properly cited and trusted.
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Cite this project
@misc{demir2026behavioral,
title = {{Behavioral Continuity, Not Family Labels: Peer-Side Detection of Silent Model Replacement}},
author = {Talha Demir},
year = {2026},
month = oct,
note = {Submitted to AI Collusion Research Sprint, an Apart Research Sprint},
howpublished = {\url{https://apartresearch.com/sprints/projects/behavioral-continuity-not-family-labels-peerside-detection-of-silent-model-replacement-m1rr}},
url = {https://apartresearch.com/sprints/projects/behavioral-continuity-not-family-labels-peerside-detection-of-silent-model-replacement-m1rr}
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