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Towards a Design Guideline for RPA Evaluation: A Survey of Large Language Model-Based Role-Playing Agents

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arxiv 2502.13012 v3 pith:5XHAYDBK submitted 2025-02-18 cs.HC cs.CL

Towards a Design Guideline for RPA Evaluation: A Survey of Large Language Model-Based Role-Playing Agents

classification cs.HC cs.CL
keywords evaluationagentdesignguidelineattributesrole-playingseventask
verification ladder T0 review T1 audit T2 compute T3 formal T4 reserved
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Role-Playing Agent (RPA) is an increasingly popular type of LLM Agent that simulates human-like behaviors in a variety of tasks. However, evaluating RPAs is challenging due to diverse task requirements and agent designs. This paper proposes an evidence-based, actionable, and generalizable evaluation design guideline for LLM-based RPA by systematically reviewing 1,676 papers published between Jan. 2021 and Dec. 2024. Our analysis identifies six agent attributes, seven task attributes, and seven evaluation metrics from existing literature. Based on these findings, we present an RPA evaluation design guideline to help researchers develop more systematic and consistent evaluation methods.

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