@inproceedings{frisch-giulianelli-2024-llm,
title = "{LLM} Agents in Interaction: Measuring Personality Consistency and Linguistic Alignment in Interacting Populations of Large Language Models",
author = "Frisch, Ivar and
Giulianelli, Mario",
editor = "Deshpande, Ameet and
Hwang, EunJeong and
Murahari, Vishvak and
Park, Joon Sung and
Yang, Diyi and
Sabharwal, Ashish and
Narasimhan, Karthik and
Kalyan, Ashwin",
booktitle = "Proceedings of the 1st Workshop on Personalization of Generative AI Systems (PERSONALIZE 2024)",
month = mar,
year = "2024",
address = "St. Julians, Malta",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2024.personalize-1.9",
pages = "102--111",
abstract = "Agent interaction has long been a key topic in psychology, philosophy, and artificial intelligence, and it is now gaining traction in large language model (LLM) research. This experimental study seeks to lay the groundwork for our understanding of dialogue-based interaction between LLMs: Do persona-prompted LLMs show consistent personality and language use in interaction? We condition GPT-3.5 on asymmetric personality profiles to create a population of LLM agents, administer personality tests and submit the agents to a collaborative writing task. We find different profiles exhibit different degrees of personality consistency and linguistic alignment in interaction.",
}
<?xml version="1.0" encoding="UTF-8"?>
<modsCollection xmlns="http://www.loc.gov/mods/v3">
<mods ID="frisch-giulianelli-2024-llm">
<titleInfo>
<title>LLM Agents in Interaction: Measuring Personality Consistency and Linguistic Alignment in Interacting Populations of Large Language Models</title>
</titleInfo>
<name type="personal">
<namePart type="given">Ivar</namePart>
<namePart type="family">Frisch</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Mario</namePart>
<namePart type="family">Giulianelli</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<originInfo>
<dateIssued>2024-03</dateIssued>
</originInfo>
<typeOfResource>text</typeOfResource>
<relatedItem type="host">
<titleInfo>
<title>Proceedings of the 1st Workshop on Personalization of Generative AI Systems (PERSONALIZE 2024)</title>
</titleInfo>
<name type="personal">
<namePart type="given">Ameet</namePart>
<namePart type="family">Deshpande</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">EunJeong</namePart>
<namePart type="family">Hwang</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Vishvak</namePart>
<namePart type="family">Murahari</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Joon</namePart>
<namePart type="given">Sung</namePart>
<namePart type="family">Park</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Diyi</namePart>
<namePart type="family">Yang</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Ashish</namePart>
<namePart type="family">Sabharwal</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Karthik</namePart>
<namePart type="family">Narasimhan</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Ashwin</namePart>
<namePart type="family">Kalyan</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<originInfo>
<publisher>Association for Computational Linguistics</publisher>
<place>
<placeTerm type="text">St. Julians, Malta</placeTerm>
</place>
</originInfo>
<genre authority="marcgt">conference publication</genre>
</relatedItem>
<abstract>Agent interaction has long been a key topic in psychology, philosophy, and artificial intelligence, and it is now gaining traction in large language model (LLM) research. This experimental study seeks to lay the groundwork for our understanding of dialogue-based interaction between LLMs: Do persona-prompted LLMs show consistent personality and language use in interaction? We condition GPT-3.5 on asymmetric personality profiles to create a population of LLM agents, administer personality tests and submit the agents to a collaborative writing task. We find different profiles exhibit different degrees of personality consistency and linguistic alignment in interaction.</abstract>
<identifier type="citekey">frisch-giulianelli-2024-llm</identifier>
<location>
<url>https://aclanthology.org/2024.personalize-1.9</url>
</location>
<part>
<date>2024-03</date>
<extent unit="page">
<start>102</start>
<end>111</end>
</extent>
</part>
</mods>
</modsCollection>
%0 Conference Proceedings
%T LLM Agents in Interaction: Measuring Personality Consistency and Linguistic Alignment in Interacting Populations of Large Language Models
%A Frisch, Ivar
%A Giulianelli, Mario
%Y Deshpande, Ameet
%Y Hwang, EunJeong
%Y Murahari, Vishvak
%Y Park, Joon Sung
%Y Yang, Diyi
%Y Sabharwal, Ashish
%Y Narasimhan, Karthik
%Y Kalyan, Ashwin
%S Proceedings of the 1st Workshop on Personalization of Generative AI Systems (PERSONALIZE 2024)
%D 2024
%8 March
%I Association for Computational Linguistics
%C St. Julians, Malta
%F frisch-giulianelli-2024-llm
%X Agent interaction has long been a key topic in psychology, philosophy, and artificial intelligence, and it is now gaining traction in large language model (LLM) research. This experimental study seeks to lay the groundwork for our understanding of dialogue-based interaction between LLMs: Do persona-prompted LLMs show consistent personality and language use in interaction? We condition GPT-3.5 on asymmetric personality profiles to create a population of LLM agents, administer personality tests and submit the agents to a collaborative writing task. We find different profiles exhibit different degrees of personality consistency and linguistic alignment in interaction.
%U https://aclanthology.org/2024.personalize-1.9
%P 102-111
Markdown (Informal)
[LLM Agents in Interaction: Measuring Personality Consistency and Linguistic Alignment in Interacting Populations of Large Language Models](https://aclanthology.org/2024.personalize-1.9) (Frisch & Giulianelli, PERSONALIZE-WS 2024)
ACL