AI RESEARCH

CoE: Collaborative Entropy for Uncertainty Quantification in Agentic Multi-LLM Systems

arXiv CS.AI

ArXi:2603.28360v1 Announce Type: new Uncertainty estimation in multi-LLM systems remains largely single-model-centric: existing methods quantify uncertainty within each model but do not adequately capture semantic disagreement across models. To address this gap, we propose Collaborative Entropy (CoE), a unified information-theoretic metric for semantic uncertainty in multi-LLM collaboration. CoE is defined on a shared semantic cluster space and combines two components: intra-model semantic entropy and inter-model divergence to the ensemble mean.