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Mind meld: agentic communication through thoughts instead of words

MBZUAI · Significant research

Research NLP LLM Partnership Arabic AI

Summary

Researchers from MBZUAI, Carnegie Mellon University, and Meta AI presented a new approach called ThoughtComm at NeurIPS 2025 where AI agents communicate through internal, latent representations instead of natural language. This framework extracts and selectively shares latent "thoughts" from agents' internal states, representing the underlying structure of their reasoning. Results show that agents coordinate more effectively, reach consensus faster, and solve problems more accurately using this method. Why it matters: Bypassing the limitations of natural language in AI communication could lead to more efficient and accurate multi-agent systems, impacting areas like robotics, collaborative AI, and distributed problem-solving.

Keywords

multi-agent communication · latent representations · MBZUAI · NeurIPS · ThoughtComm

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