Chorus of the Past: Toward Designing a Multi-agent Conversational Reminiscence System with Digital Artifacts for Older Adults

Reminiscence has been shown to provide benefits for older adults, but traditionally relies on personal photos as memory cues and interactions with real people who may not always be available. We present ReminiBuddy, a novel LLM-powered multi-agent conversational system, which allows older adults to engage with two distinct agents - one embodying an older identity and the other a younger identity - while using not only personal photos but also 3D models of generic nostalgic objects as memory cues. Our study, with older adult participants, found that the conversational approach both enjoyable and beneficial for reminiscence. While the younger agent was perceived as more emotionally engaging, the older one fostered greater resonance in content. Personal photos prompted autobiographical memories, whereas 3D generic nostalgic objects evoked shared memories of an era, contributing to a more multifaceted reminiscence experience. We further present design implications for better supporting older adults in reminiscing with LLM-powered conversational agents.

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Publication Details

Published
2025-04-24
DOI
https://doi.org/10.1145/3706598.3713810
Citations
1
Primary Topic
Technology Use by Older Adults
Type
article
Field-Weighted Citation Impact
5.59
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article

Chorus of the Past: Toward Designing a Multi-agent Conversational Reminiscence System with Digital Artifacts for Older Adults

Nianlong Li, Zhongyue Zhang, Mingming Fan, Qianying Wang et al.
1 citations
Technology Use by Older Adults
5.59
article

Chorus of the Past: Toward Designing a Multi-agent Conversational Reminiscence System with Digital Artifacts for Older Adults

Nianlong Li, Zhongyue Zhang, Mingming Fan, Qianying Wang, Mengyang Wang, Jingwei Sun, Yu Zhang, Yan Xiang, Liuxin Zhang, Zhangwei Lu
article en
1 citations

Abstract

Reminiscence has been shown to provide benefits for older adults, but traditionally relies on personal photos as memory cues and interactions with real people who may not always be available. We present ReminiBuddy, a novel LLM-powered multi-agent conversational system, which allows older adults to engage with two distinct agents - one embodying an older identity and the other a younger identity - while using not only personal photos but also 3D models of generic nostalgic objects as memory cues. Our study, with older adult participants, found that the conversational approach both enjoyable and beneficial for reminiscence. While the younger agent was perceived as more emotionally engaging, the older one fostered greater resonance in content. Personal photos prompted autobiographical memories, whereas 3D generic nostalgic objects evoked shared memories of an era, contributing to a more multifaceted reminiscence experience. We further present design implications for better supporting older adults in reminiscing with LLM-powered conversational agents.

Lenovo (China) (CN), Southeast University (CN)
Quality Education
Openalex Percentile: Top 7%
Technology Use by Older Adults
5.59
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