Role-Playing Evaluation for Large Language Models

Yassine El Boudouri, Walter Nuninger, Julian Alvarez, Yvan Peter

Role-Playing Evaluation for Large Language Models: 5 upvotes on Hugging Face Daily Papers, #26 of 42 papers on 2025-06-02. Day-by-day upvote history.

Large Language Models (LLMs) demonstrate a notable capacity for adopting personas and engaging in role-playing. However, evaluating this ability presents significant challenges, as human assessments are resource-intensive and automated evaluations can be biased. To address this, we introduce Role-Playing Eval (RPEval), a novel benchmark designed to assess LLM role-playing capabilities across four key dimensions: emotional understanding, decision-making, moral alignment, and in-character consistency. This article details the construction of RPEval and presents baseline evaluations. Our code and dataset are available at https://github.com/yelboudouri/RPEval

Paper page on Hugging Face · arXiv

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