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Trust, but verify

Author

Listed:
  • Michael J. Yuan
  • Carlos Campoy
  • Sydney Lai
  • James Snewin
  • Ju Long

Abstract

Decentralized AI agent networks, such as Gaia, allows individuals to run customized LLMs on their own computers and then provide services to the public. However, in order to maintain service quality, the network must verify that individual nodes are running their designated LLMs. In this paper, we demonstrate that in a cluster of mostly honest nodes, we can detect nodes that run unauthorized or incorrect LLM through social consensus of its peers. We will discuss the algorithm and experimental data from the Gaia network. We will also discuss the intersubjective validation system, implemented as an EigenLayer AVS to introduce financial incentives and penalties to encourage honest behavior from LLM nodes.

Suggested Citation

  • Michael J. Yuan & Carlos Campoy & Sydney Lai & James Snewin & Ju Long, 2025. "Trust, but verify," Papers 2504.13443, arXiv.org.
    • Handle: RePEc:arx:papers:2504.13443
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    File URL: http://arxiv.org/pdf/2504.13443
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