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Sprint projectOct 24, 2026India

Beyond The Signal

Vivek Visave · Team Arsencio

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

This project examines how to assess convincing evidence of steganographic collusion in multi-agent AI systems. Using the existing Audit the Whisper benchmark's reported detector metrics, I compared false-positive rates, true-positive rates, ROC AUC, and detector-combination results. The findings reveal substantial variation in detector performance: some methods report perfect separation, while others exhibit low sensitivity or extremely high false-positive rates. Detector combinations show promising sensitivity, but their reliability requires further validation. The analysis highlights that suspicious communication, correlated actions, or harmful outcomes alone are insufficient to establish collusion. Reliable auditing requires considering multiple evidence sources, alternative explanations, and calibration limitations before drawing conclusions.

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  1. 1Negligible. No clear problem addressed, or no meaningful novelty.
  2. 2Limited. Addresses a real problem but with a generic or well-trodden approach. Incremental at best.
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  2. 2Weak. Approach has significant gaps: missing validation, flawed experimental design, or incomplete implementation.
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Cite this project

@misc{visave2026beyond,
  title = {{Beyond The Signal}},
  author = {Vivek Visave},
  year = {2026},
  month = oct,
  note = {Submitted to AI Collusion Research Sprint, an Apart Research Sprint},
  howpublished = {\url{https://apartresearch.com/sprints/projects/beyond-the-signal-ht9e}},
  url = {https://apartresearch.com/sprints/projects/beyond-the-signal-ht9e}
}