Trust, but verify
Not on the map. Why?
Abstract (arXiv)
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.
Key facts. Cited by 2 papers in the map (data through 14 Oct 2026). Builds on 9 of its 43 references that are in the map. First posted on arXiv 18 Apr 2025.
Builds on
9 of 43 references.
References · 9
- 2024The Llama 3 Herd of Modelscited by 14,715
- 2020Dense Passage Retrieval for Open-Domain Question Answeringcited by 3,824
- 2023A Survey of Large Language Modelscited by 2,576
- 2024Qwen2 Technical Reportcited by 2,120
- 2024Gemma: Open Models Based on Gemini Research and Technologycited by 916
- 2024A Survey on Large Language Models for Code Generationcited by 658
- 2024Nomic Embed: Training a Reproducible Long Context Text Embeddercited by 265
- 2024zkLLM: Zero Knowledge Proofs for Large Language Modelscited by 51
- 2024Trust the Process: Zero-Knowledge Machine Learning to Enhance Trust in Generative AI Interactionscited by 6
Built on by
Citing papers per year: 2025: 2.
2 papers.