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arXiv cs.AI · 2026-08-12 00:00 UTC
research

Post-Hoc Sparse Coding of Latent Communication Between Vision-Language Model Agents

arXiv:2608.10198v1 Announce Type: new Abstract: Latent-space communication allows heterogeneous vision-language model agents to exchange continuous representations without serializing visual and reasoning states into text. Vision Wormhole realizes this approach by translating visual features into a universal latent representation that can be consumed by another model, but every message is transported as a dense tensor of the same size regardless of its content. A fixed-capacity dense tensor therefore need not have a fixed effective information density: some messages may use only a small fracti

Why it matters

Sparse coding of inter-agent latent communication offers tools to interpret coordination, enabling debugging and governance of multi-agent VLM systems.

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Published to Cognify News · Week 33, 2026