Estimation of Propagated Risk in LLM-based Multi-Agent Systems

arXiv cs.AIOctober 27, 2026en

arXiv cs.AI

AI Global Wire

arXiv:2610.33282v1 Announce Type: new Abstract: Large Language Model (LLM) based multi-agent systems introduce a distinctive reliability challenge in which actions taken by upstream agents can affect the correctness of downstream agents. While prior work has investigated error propagation and developed methods for estimating uncertainty inherited from upstream agents, existing approaches do not explicitly model how realized sender-receiver interactions contribute to downstream error risk under different sender correctness states. In this work, we study agent-level error-risk estimation from multi-agent execution traces. We propose Interaction-Effect Propagation (IE-Prop), an interaction-cond

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