Papers by Daniel Barcklow

1 papers
GRAVITY: A Framework for Personalized Text Generation via Profile-Grounded Synthetic Preferences (2026.eacl-long)

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Challenge: Personalization in LLMs often relies on costly human feedback or interaction logs, limiting scalability and neglecting deeper user attributes.
Approach: They propose a framework for generating synthetic, profile-grounded preference data that captures users’ interests, values, beliefs, and personality traits.
Outcome: The proposed framework improves on book descriptions for 400 Amazon users across multiple cultures, with user studies showing that outputs are preferred over 86% of the time.

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