Beyond the Transcript: Detecting Covert Co ordination in Latent Multi-Agent Communication
Language-model agents can communicate through continuous hidden states that are invisible in public transcripts, creating opportunities for covert harmful coordination. We introduce Verifiable Latent Alignments (VLA), an activation-aware framework for monitoring and steering these private communication channels. For every monitored decision, VLA links the private latent-state record and channel status to the resulting public action using a shared event identifier, enabling matched causal analysis. Our first contribution is a neutral-only three-layer monitor combining representation anomaly detection, counterfactual action-distribution influence, and sparse-autoencoder interpretation suppo...
| Authors | Ramneet Kaur, Pradyumna Chari, Ramesh Raskar et al. |
|---|---|
| Primary category | cs.AI |
| Published | 19 August 2026 |
| Last updated at source | 19 August 2026 |
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