AI RESEARCH
Belief Engine: Configurable and Inspectable Stance Dynamics in Multi-Agent LLM Deliberation
arXiv CS.AI
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ArXi:2605.15343v1 Announce Type: new LLM-based agents are increasingly used to simulate deliberative interactions such as negotiation, conflict resolution, and multi-turn opinion exchange. Yet generated transcripts often do not reveal why an agent's stance changes: movement may reflect evidence uptake, anchoring, role drift, echoing, or changed prompt and retrieval context. We