Chameleon LLMs: User Personas Influence Chatbot Personality Shifts
Authors: Jane Xing, Tianyi Niu, Shashank Srivastava
Accepted at: acl25


Metareview score: 4
Metareview: This paper explores the extent to which LLMs shift their personality in response to user interactions.  Conversations are simulated between user and chatbot, with both roles played by LLMs. In each simulated conversation, the "user" is assigned a personality, and both user and chatbot are given personality tests before and after the conversation, and changes in chatbot personality are analyzed. Additional experiments were conducted to measure the manipulability of the influence effect, where the chatbot was instructed to either "amplify mirroring" or "resist mirroring".
Summary of reasons to publish: The experimental setup is novel and creative, and the results are compelling. Reviewer y7Jt notes that "The finding that personality shifts occur is intriguing and has implications for future research". The personality shifts also have interesting variations: Agreeableness, Extraversion, and Conscientiousness exhibit more change, with less for Emotional Stability and Intellect. Furthermore, it was found, with respect to Extraversion and Imagination, that large models shift more than smaller models. An additional experiment showed that it was possible to amplify the mirroring effect (with GPT-4o mini) but not to resist that effect.