@inproceedings{xie-etal-2025-ipet,
title = "i{PET}: An Interactive Emotional Companion Dialogue System with {LLM}-Powered Virtual Pet World Simulation",
author = "Xie, Zheyong and
Cao, Shaosheng and
Liu, Zuozhu and
Ye, Zheyu and
Niu, Zihan and
Lu, Chonggang and
Xu, Tong and
Chen, Enhong and
Xu, Zhe and
Hu, Yao and
Lu, Wei",
editor = "Mishra, Pushkar and
Muresan, Smaranda and
Yu, Tao",
booktitle = "Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 3: System Demonstrations)",
month = jul,
year = "2025",
address = "Vienna, Austria",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2025.acl-demo.40/",
doi = "10.18653/v1/2025.acl-demo.40",
pages = "416--425",
ISBN = "979-8-89176-253-4",
abstract = "The rapid advancement of large language models (LLMs) has unlocked transformative potential for role-playing emotional companion products, enabling systems that support emotional well-being, educational development, and therapeutic applications. However, existing approaches often lack sustained personalization and contextual adaptability, limiting their effectiveness in real-world settings. In this paper, we introduce iPET, an LLM-powered virtual pet agent designed to enhance user engagement through rich, dynamic pet behaviors and interactions tailored to individual preferences. iPET comprises three core components: a dialogue module that instantiates virtual pet agents for emotionally interactive conversations; a memory module that stores and synthesizes records of both agent and user experiences; and a world simulation module that generates diverse, preference-driven pet behaviors guided by high-level reflections. Deployed for over 200 days in a real-world, non-commercial product, iPET has served millions of users {--} providing emotional support to psychologically distressed individuals and demonstrating its effectiveness in practical applications."
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<abstract>The rapid advancement of large language models (LLMs) has unlocked transformative potential for role-playing emotional companion products, enabling systems that support emotional well-being, educational development, and therapeutic applications. However, existing approaches often lack sustained personalization and contextual adaptability, limiting their effectiveness in real-world settings. In this paper, we introduce iPET, an LLM-powered virtual pet agent designed to enhance user engagement through rich, dynamic pet behaviors and interactions tailored to individual preferences. iPET comprises three core components: a dialogue module that instantiates virtual pet agents for emotionally interactive conversations; a memory module that stores and synthesizes records of both agent and user experiences; and a world simulation module that generates diverse, preference-driven pet behaviors guided by high-level reflections. Deployed for over 200 days in a real-world, non-commercial product, iPET has served millions of users – providing emotional support to psychologically distressed individuals and demonstrating its effectiveness in practical applications.</abstract>
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%0 Conference Proceedings
%T iPET: An Interactive Emotional Companion Dialogue System with LLM-Powered Virtual Pet World Simulation
%A Xie, Zheyong
%A Cao, Shaosheng
%A Liu, Zuozhu
%A Ye, Zheyu
%A Niu, Zihan
%A Lu, Chonggang
%A Xu, Tong
%A Chen, Enhong
%A Xu, Zhe
%A Hu, Yao
%A Lu, Wei
%Y Mishra, Pushkar
%Y Muresan, Smaranda
%Y Yu, Tao
%S Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 3: System Demonstrations)
%D 2025
%8 July
%I Association for Computational Linguistics
%C Vienna, Austria
%@ 979-8-89176-253-4
%F xie-etal-2025-ipet
%X The rapid advancement of large language models (LLMs) has unlocked transformative potential for role-playing emotional companion products, enabling systems that support emotional well-being, educational development, and therapeutic applications. However, existing approaches often lack sustained personalization and contextual adaptability, limiting their effectiveness in real-world settings. In this paper, we introduce iPET, an LLM-powered virtual pet agent designed to enhance user engagement through rich, dynamic pet behaviors and interactions tailored to individual preferences. iPET comprises three core components: a dialogue module that instantiates virtual pet agents for emotionally interactive conversations; a memory module that stores and synthesizes records of both agent and user experiences; and a world simulation module that generates diverse, preference-driven pet behaviors guided by high-level reflections. Deployed for over 200 days in a real-world, non-commercial product, iPET has served millions of users – providing emotional support to psychologically distressed individuals and demonstrating its effectiveness in practical applications.
%R 10.18653/v1/2025.acl-demo.40
%U https://aclanthology.org/2025.acl-demo.40/
%U https://doi.org/10.18653/v1/2025.acl-demo.40
%P 416-425
Markdown (Informal)
[iPET: An Interactive Emotional Companion Dialogue System with LLM-Powered Virtual Pet World Simulation](https://aclanthology.org/2025.acl-demo.40/) (Xie et al., ACL 2025)
ACL
- Zheyong Xie, Shaosheng Cao, Zuozhu Liu, Zheyu Ye, Zihan Niu, Chonggang Lu, Tong Xu, Enhong Chen, Zhe Xu, Yao Hu, and Wei Lu. 2025. iPET: An Interactive Emotional Companion Dialogue System with LLM-Powered Virtual Pet World Simulation. In Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 3: System Demonstrations), pages 416–425, Vienna, Austria. Association for Computational Linguistics.