@inproceedings{3fed90f3950c41f49e35aa9c22da15f1,
title = "Conformity, Confabulation, and Impersonation: Persona Inconstancy in Multi-Agent LLM Collaboration",
abstract = "This study explores the sources of instability in maintaining cultural personas and opinions within multi-agent LLM systems. Drawing on simulations of inter-cultural collaboration and debate, we analyze agents{\textquoteright} pre- and post-discussion private responses alongside chat transcripts to assess the stability of cultural personas and the impact of opinion diversity on group outcomes. Our findings suggest that multi-agent discussions can encourage collective decisions that reflect diverse perspectives, yet this benefit is tempered by the agents{\textquoteright} susceptibility to conformity due to perceived peer pressure and challenges in maintaining consistent personas and opinions. Counterintuitively, instructions that encourage debate in support of one{\textquoteright}s opinions increase the rate of inconstancy. Without addressing the factors we identify, the full potential of multi-agent frameworks for producing more culturally diverse AI outputs will remain untapped.",
author = "Razan Baltaji and Babak Hemmatian and Varshney, \{Lav R.\}",
note = "Publisher Copyright: {\textcopyright} 2024 Association for Computational Linguistics.; 2nd Workshop on Cross-Cultural Considerations in NLP, C3NLP 2024 ; Conference date: 16-08-2024",
year = "2024",
language = "English",
series = "C3NLP 2024 - 2nd Workshop on Cross-Cultural Considerations in NLP, Proceedings of the Workshop",
publisher = "Association for Computational Linguistics (ACL)",
pages = "17--31",
editor = "Vinodkumar Prabhakaran and Sunipa Dev and Luciana Benotti and Daniel Hershcovich and Laura Cabello and Yong Cao and Ife Adebara and Li Zho",
booktitle = "C3NLP 2024 - 2nd Workshop on Cross-Cultural Considerations in NLP, Proceedings of the Workshop",
}