Interlat: Enabling Agents to Communicate Entirely in Latent Space

Jul 14, 2026

Researchers introduce Interlat, a paradigm where LLM-based agents communicate using continuous latent states rather than natural language. Inspired by telepathy, this approach allows agents to share internal representations directly, bypassing the limitations of token-based communication. Experiments show that Interlat outperforms chain-of-thought prompting and single-agent baselines, and that compressing latent messages can accelerate inference by up to 24x while maintaining competitive performance.

Why it matters: This work demonstrates a novel and potentially more efficient method for multi-agent communication, challenging the dominance of natural language and opening new directions for collaborative AI systems.

Full story at: arXiv Multiagent Systems ↗