Learning Preference Adaptation for Large Language Model Personalization via Verbal Reinforcement Learning
An extended faithfulness analysis shows that the refined profiles remain largely grounded in the source preferences while preserving task-relevant personalization signals, suggesting that profile-side adaptation serves as a practical complement to universal memory construction for lifelong personalized agents.