T ailor RPA : A Retrieval-Based Framework for Eliciting Personalized and Coherent Role-Playing Agents in General Domain (2025)

Abstract: Recent advancements of general domain oriented Role-playing Agents (RPAs) have enabled the agents to maintain character properties in a wide spectrum of daily tasks beyond mere scenario based chit-chatting. Nonetheless, current works lacks consideration of replicating internal properties of characters like fine-grained memories, and failed to take account of aligning with the knowledge boundary of each character, resulting in degraded personalization and proneness to character hallucination in general domain. To address these problems, we draw inspirations from the context effect theory and propose a retrieval-based framework TailorRPA to harvest tailored general domain instructions to improve integration of fine-grained memories and incorporate general-domain protective queries to help shape the character-wise knowledge boundary, alleviating character hallucination. Based on the framework, we developed a role-playing dataset TailorGen, comprising both role-specific and general-domain instructions. Through empirical experiments, we proved the superiority of TailorRPA in eliciting general domain role-playing capabilities and alleviating character hallucination compared to baseline methods, and explored the existence of character hallucination in state-of-the-art proprietary models through empirical experiments, underlining the importance of our work.

## introduction the strong generalization ability of large language models (llms) has sparked vast research interest in role-playing agents (rpas), aiming to mimic the tone, as well as the personality of a designated character 1 @xcite @xcite . inspired by the concept that a comprehensive role-playing agent ## methodology figure 2 illustrates the overall framework of our proposed dataset synthesis framework, tailor-rpa. it begins with the collection of characters' information, followed by the generation of rolespecific questions and collection of role-oriented general-domain queries, resulting in a comprehensive multi-domain dataset to enable llms to elicit role-playing abilities while mitigating character hallucination. ## conclusion in this paper, we propose tailorrpa, a novel retrieval-based framework aimed at eliciting highquality general-domain instructions tailored to diverse backgrounds of characters. we constructed a multi-domain role-playing dataset tai-lorgen based on the basis on the framework, and incorporated protective queries introduced to mitigate general-domain character hallucination. extensive experiments demonstrates the effectiveness of our dataset in eliciting general-domain roleplaying ability and hallucination mitigation. we hope our work will motivate more follow-up researches on general-domain role-playing and character hallucination.