TAP-PER encodes user preferences as lightweight learnable prefix embeddings that outperform prompt-based and adapter-based baselines on LaMP tasks with 130x fewer per-user parameters.
arXiv preprint arXiv:2509.23767 , year=
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Beyond Retrieval: Learning Compact User Representations for Scalable LLM Personalization
TAP-PER encodes user preferences as lightweight learnable prefix embeddings that outperform prompt-based and adapter-based baselines on LaMP tasks with 130x fewer per-user parameters.