Yuxin Chen
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The paper introduces PARL, a framework that learns personalized evaluation rubrics directly from raw user interaction histories to accurately assess how well LLM outputs align with subjective, user-specific preferences.
The paper introduces GenPT, a Generative Projective Testing framework, which demonstrates superior reliability and resistance to social-desirability bias compared to traditional self-report questionnaires when assessing LLM psychological states.
Papers
GenPT: Beyond Self-Report for Reliable LLM Psychometrics via Generative Projective Testing
Ming Wang, Shuang Wu, Bixuan Wang, Lu Lin +6 more
The paper introduces GenPT, a Generative Projective Testing framework, which demonstrates superior reliability and resistance to social-desirability bias compared to traditional self-report questionna…