CloChat: Understanding How People Customize, Interact, and Experience Personas in Large Language Models

Juhye Ha, Hyeon Jeon, Daeun Han, Jinwook Seo, Changhoon Oh

Research output: Chapter in Book/Report/Conference proceedingConference contribution

4 Citations (Scopus)

Abstract

Large language models (LLMs) have facilitated significant strides in generating conversational agents, enabling seamless, contextually relevant dialogues across diverse topics. However, the existing LLM-driven conversational agents have fixed personalities and functionalities, limiting their adaptability to individual user needs. Creating personalized agent personas with distinct expertise or traits can address this issue. Nonetheless, we lack knowledge of how people customize and interact with agent personas. In this research, we investigated how users customize agent personas and their impact on interaction quality, diversity, and dynamics. To this end, we developed CloChat, an interface supporting easy and accurate customization of agent personas in LLMs. We conducted a study comparing how participants interact with CloChat and ChatGPT. The results indicate that participants formed emotional bonds with the customized agents, engaged in more dynamic dialogues, and showed interest in sustaining interactions. These findings contribute to design implications for future systems with conversational agents using LLMs.

Original languageEnglish
Title of host publicationCHI 2024 - Proceedings of the 2024 CHI Conference on Human Factors in Computing Sytems
PublisherAssociation for Computing Machinery
ISBN (Electronic)9798400703300
DOIs
Publication statusPublished - 2024 May 11
Event2024 CHI Conference on Human Factors in Computing Sytems, CHI 2024 - Hybrid, Honolulu, United States
Duration: 2024 May 112024 May 16

Publication series

NameConference on Human Factors in Computing Systems - Proceedings

Conference

Conference2024 CHI Conference on Human Factors in Computing Sytems, CHI 2024
Country/TerritoryUnited States
CityHybrid, Honolulu
Period24/5/1124/5/16

Bibliographical note

Publisher Copyright:
© 2024 Copyright held by the owner/author(s)

All Science Journal Classification (ASJC) codes

  • Software
  • Human-Computer Interaction
  • Computer Graphics and Computer-Aided Design

Fingerprint

Dive into the research topics of 'CloChat: Understanding How People Customize, Interact, and Experience Personas in Large Language Models'. Together they form a unique fingerprint.

Cite this