2025
ACL
ACL 2025
Towards a Design Guideline for RPA Evaluation: A Survey of Large Language Model-Based Role-Playing Agents
Abstract
AbstractRole-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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Keyword Pioneer
— evaluation design
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Cross-Pollinator
— Artificial Intelligence, Computer Science, Computer Vision, Data Science & Analytics, Deep Learning, Interdisciplinary, Machine Learning, Natural Language Processing, Reinforcement Learning, Robotics, Speech & Audio