AI RESEARCH
Beyond Cooperative Simulators: Generating Realistic User Personas for Robust Evaluation of LLM Agents
arXiv CS.AI
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ArXi:2605.12894v1 Announce Type: new Large Language Model (LLM) agents are increasingly deployed in settings where they interact with a wide variety of people, including users who are unclear, impatient, or reluctant to share information. However, collecting real interaction data at scale remains expensive. The field has turned to LLM-based user simulators as stand-ins, but these simulators inherit the behavior of their underlying models: cooperative and homogeneous.