Changlin Zhao

Beyond Retrieval: Learning Compact User Representations for Scalable LLM Personalization

TAP-PER (Temporal Attentive Prefix for PERsonalization), a prefix-based framework that encodes user preferences as learnable representations, avoiding the serialization of user histories into prompts and replacing heavy per-user adapters with lightweight user-state prefix embeddings, is proposed.