InCharacter: Evaluating Personality Fidelity in Role-Playing Agents through Psychological Interviews

The procedure of personality tests on RPAs. To evaluate the personality fidelity of RPAs, we ap- ply various scales to measure their personalities and compare the results with the personality labels of the characters.

Abstract

Role-playing agents (RPAs), powered by large language models, have emerged as a flourishing field of applications. However, a key challenge lies in assessing whether RPAs accurately reproduce the personas of target characters, namely their character fidelity. Existing methods mainly focus on the knowledge and linguistic patterns of characters. This paper, instead, introduces a novel perspective to evaluate the personality fidelity of RPAs with psychological scales. Overcoming drawbacks of previous self-report assessments on RPAs, we propose InCharacter, namely Interviewing Character agents for personality tests. Experiments include various types of RPAs and LLMs, covering 32 distinct characters on 14 widely used psychological scales. The results validate the effectiveness of InCharacter in measuring RPA personalities. Then, with InCharacter, we show that state-of-the-art RPAs exhibit personalities highly aligned with the human-perceived personalities of the characters, achieving an accuracy up to 80.7%.

Type
Publication
The 62nd Annual Meeting of the Association for Computational Linguistics (ACL 2024)
Jiangjie Chen
Jiangjie Chen
Ph.D. Candidate

His research interests mainly include natural language reasoning and large language models.