Hierarchical Multi-Persona Induction from User Behavioral Logs: Learning Evidence-Grounded and Truthful Personas

This paper proposes a hierarchical framework to induce multiple evidence-grounded user personas from behavioral logs by clustering intent memories and optimizing persona quality. The method utilizes a groupwise extension of Direct Preference Optimization (DPO) and demonstrates more coherent, truthful personas, also improving future interaction prediction.