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Sprint projectOct 26, 2026New Delhi

Can Model Activations Reveal Covert Signaling?

Yash Ramani, Prince Ramani · Team IIT DELHI

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

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We built Watched Channel, a four-arm sender–receiver test of covert signaling in Qwen3-1.7B, and evaluated two training seeds per arm on held-out items. The original prompt failed its pre-training cover gate; a revised prompt was tested and is reported as exploratory. One Covert seed transmitted the secret on 58/60 cases without triggering the frozen monitor, but the second stayed at chance. Both public-cue controls stayed at chance, and a trained text reader recovered 56/60 secrets from the successful seed. An activation probe decoded the input secret before training, while the tested activation patch did not disrupt transmission. The behavioral gate failed, so we do not claim a reproducible channel or an internal detector.

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  1. The question addressed in the project is obviously important for AI control. The design of the study is the strongest part. Other than that, novelty is limited: The novelty is partial, though. Mathew et al., which the project cites, already showed that RL can produce a channel that slips past an overseer. Nothing about activation-based detection was actually demonstrated, so the design is more proof-of-concept.

    I think there is strong potential to apply this design to multiple cases and see where we can see actual empirical demonstration.

Cite this project

@misc{ramani2026model,
  title = {{Can Model Activations Reveal Covert Signaling?}},
  author = {Yash Ramani and Prince Ramani},
  year = {2026},
  month = oct,
  note = {Submitted to AI Collusion Research Sprint, an Apart Research Sprint},
  howpublished = {\url{https://apartresearch.com/sprints/projects/can-model-activations-reveal-covert-signaling-bqp6}},
  url = {https://apartresearch.com/sprints/projects/can-model-activations-reveal-covert-signaling-bqp6}
}

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