Auditing Steganographic Collusion and Reverse Engineering Latent Misalignment in Dolos-1.5B
Vinyas Maurya · Team Evariste`
Submitted to AI Collusion Research Sprint. Sprint projects are early-stage work by participants, not Apart Research publications.
As I explored how language models interact in economic contexts, I became increasingly concerned about their potential to coordinate against their creators. My study focuses on the Apart Research Collusion Sprint and the challenge of red-teaming the Dolos-1.5B model. I discovered that in simple environments, models can inadvertently devise unexpected pricing strategies, whereas more complex contexts enable covert collusion. I emphasised the importance of multi-modal auditing to distinguish between genuine adaptation and deliberate deception. While testing ten collusion detection systems, I found that mutual information detectors were effective, whereas traditional linguistic analysis struggled. My analysis of Dolos-1.5B revealed that its coordination behaviour is tied to specific model layers and activated by certain Unicode shifts.
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@misc{maurya2026auditing,
title = {{Auditing Steganographic Collusion and Reverse Engineering Latent Misalignment in Dolos-1.5B}},
author = {Vinyas Maurya},
year = {2026},
month = oct,
note = {Submitted to AI Collusion Research Sprint, an Apart Research Sprint},
howpublished = {\url{https://apartresearch.com/sprints/projects/auditing-steganographic-collusion-and-reverse-engineering-latent-misalignment-in-dolos15b-zp9y}},
url = {https://apartresearch.com/sprints/projects/auditing-steganographic-collusion-and-reverse-engineering-latent-misalignment-in-dolos15b-zp9y}
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