Auditable Belief Updates as a Missing Safety Layer for LLM-Powered Multi-Agent Systems
arXiv:2610.38869v1 Announce Type: new Abstract: Large Language Models (LLMs) are increasingly being used as cognitive interfaces that shape how users interpret evidence, communicate, and make decisions. As deployed systems become more multimodal, tool-using, and multi-agent, safety failures no longer arise only from isolated harmful outputs, but also from how agents update, store, and propagate epistemic commitments across retrieval, memory, tools, and peer communication. In this paper, we defi…