A new hierarchical framework aggregates user behavioral logs into intent memories to generate evidence-grounded personas. Researchers used a groupwise extension of Direct Preference Optimization to maximize cluster cohesion and truthfulness. This method reduces noise in user modeling. It provides a more reliable way to verify persona quality beyond downstream utility.