Cited by 12

The DOI matches its Crossref record; 9 of the 9 references it cites were found in a registry or an index.

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

Sun, Jingwei, Zhang, Zhongyue, Wang, Mengyang, Li, Nianlong, Lu, Zhangwei, Xiang, Yan, Zhang, Liuxin, Zhang, Yu, Wang, Qianying, Fan, Mingming·2025·Proceedings of the 2025 CHI Conference on Human Factors in Computing Systems

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.

Overview

Integrity signals

Registry

Crossref · 10.1145/3706598.3713810

Cites

9 of 9 references verified0 citation errors · 0 not checkable

Statistics

Recomputing p-values needs the paper’s full text.

Verification

Claims the paper makes

This paper’s full text isn’t openly available, so its claims and self-check weren’t run. The registry and citation checks still apply.

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

Citations

Cites

Show all 9 references

Research works printed but not linked: 41

  1. Alaa Abd-alrazaq Dari Alhuwail Eiman Al-Jafar Arfan Ahmed Farag Shuweihdi Shuja Mohd Reagu and Mowafa Househ. 2022. The Effectiveness of Serious Games in Improving Memory Among Older Adults With Cognitive Impairment: Systematic Review and Meta-analysis. JMIR Serious Games 10 3 (Aug. 2022) e35202. 10.2196/35202 · DOI
  2. Arlene J. Astell Maggie P. Ellis Norman Alm Richard Dye and Gary Gowans. 2010. Stimulating people with dementia to reminisce using personal and generic photographs. International Journal of Computers in Healthcare 1 2 (2010) 177. 10.1504/IJCIH.2010.037461 · DOI
  3. 10.1145/3180308.3180330 · DOI
  4. Benett Axtell and Cosmin Munteanu. 2019. Back to Real Pictures: A Cross-generational Understanding of Users’ Mental Models of Photo Cloud Storage. Proceedings of the ACM on Interactive Mobile Wearable and Ubiquitous Technologies 3 3 (Sept. 2019) 1–24. 10.1145/3351232 · DOI
  5. 10.1145/3290607.3313272 · DOI
  6. 10.1145/3491102.3517692 · DOI
  7. Steven Baker Ryan M. Kelly Jenny Waycott Romina Carrasco Roger Bell Zaher Joukhadar Thuong Hoang Elizabeth Ozanne and Frank Vetere. 2021. School’s Back: Scaffolding Reminiscence in Social Virtual Reality with Older Adults. Proceedings of the ACM on Human-Computer Interaction 4 CSCW3 (Jan. 2021) 1–25. 10.1145/3434176 · DOI
  8. 10.1145/3372278.3391927 · DOI
  9. 10.1109/ICASSP40776.2020.9053159 · DOI
  10. Maria Cotelli Rosa Manenti and Orazio Zanetti. 2012. Reminiscence therapy in dementia: A review. Maturitas 72 3 (July 2012) 203–205. 10.1016/j.maturitas.2012.04.008 · DOI
  11. Burcu Demiray Marianne Mischler and Mike Martin. 2019. Reminiscence in Everyday Conversations: A Naturalistic Observation Study of Older Adults. The Journals of Gerontology: Series B 74 5 (June 2019) 745–755. 10.1093/geronb/gbx141 · DOI
  12. 10.18653/v1/2023.acl-long.225 · DOI
  13. 10.1007/978-3-030-77080-8_27 · DOI
  14. D Greenberg M Eacott D Brechin and D Rubin. 2005. Visual memory loss and autobiographical amnesia: a case study. Neuropsychologia 43 10 (2005) 1493–1502. 10.1016/j.neuropsychologia.2004.12.009 · DOI
  15. 10.1007/978-3-031-61281-7_24 · DOI
  16. 10.1145/3613905.3650979 · DOI
  17. 10.1145/3613904.3642800 · DOI
  18. 10.1145/3411764.3445688 · DOI
  19. Takeshi Kojima, Shixiang (Shane) Gu, Machel Reid, Yutaka Matsuo, and Yusuke Iwasawa. 2022. Large Language Models are Zero-Shot Reasoners. In Advances in Neural Information Processing Systems , S. Koyejo, S. Mohamed, A. Agarwal, D. Belgrave, K. Cho, and A. Oh (Eds.), Vol. 35. Curran Associates, Inc., 22199–22213. https://proceedings.neurips.cc/paper_files/paper/2022/file/8bb0d291acd4acf06ef112099c16f326-Paper-Conference.pdf
  20. 10.1145/3613904.3642168 · DOI
  21. 10.1145/3477495.3532001 · DOI
  22. Zisu Li Li Feng Chen Liang Yuru Huang and Mingming Fan. 2023. Exploring the Opportunities of AR for Enriching Storytelling with Family Photos between Grandparents and Grandchildren. Proceedings of the ACM on Interactive Mobile Wearable and Ubiquitous Technologies 7 3 (Sept. 2023) 1–26. 10.1145/3610903 · DOI
  23. Amna Liaqat Benett Axtell and Cosmin Munteanu. 2022. "With a hint she will remember": Collaborative Storytelling and Culture Sharing between Immigrant Grandparents and Grandchildren Via Magic Thing Designs. Proc. ACM Hum.-Comput. Interact. 6 CSCW2 Article 268 (nov 2022) 37 pages. 10.1145/3555158 · DOI
  24. Siân E. Lindley. 2012. Before I Forget: From Personal Memory to Family History. Human–Computer Interaction 27 1-2 (2012) 13–36. 10.1080/07370024.2012.656065 · DOI
  25. 10.1145/2441776.2441802 · DOI
  26. 10.18653/v1/2023.emnlp-main.814 · DOI · Paper page
  27. Wilson Tam Sum Nok Poon Rathi Mahendran Ee Heok Kua and Xi Vivien Wu. 2021. The effectiveness of reminiscence-based intervention on improving psychological well-being in cognitively intact older adults: A systematic review and meta-analysis. International Journal of Nursing Studies 114 (Feb. 2021) 103847. 10.1016/j.ijnurstu.2020.103847 · DOI
  28. 10.1145/1377999.1378023 · DOI
  29. 10.1145/2470654.2466215 · DOI
  30. 10.1145/2212776.2223698 · DOI
  31. Seiki Tokunaga Kazuhiro Tamura and Mihoko Otake-Matsuura. 2021. A Dialogue-Based System with Photo and Storytelling for Older Adults: Toward Daily Cognitive Training. Frontiers in Robotics and AI 8 (June 2021) 644964. 10.3389/frobt.2021.644964 · DOI
  32. Xin Wang Juan Li Tianyi Liang Wordh Ul Hasan Kimia Tuz Zaman Yang Du Bo Xie and Cui Tao. 2024. Promoting Personalized Reminiscence Among Cognitively Intact Older Adults Through an AI-Driven Interactive Multimodal Photo Album: Development and Usability Study. JMIR aging 7 (Jan. 2024) e49415. 10.2196/49415 · DOI
  33. J. D. Webster. 1993. Construction and Validation of the Reminiscence Functions Scale. Journal of Gerontology 48 5 (Sept. 1993) P256–P262. 10.1093/geronj/48.5.P256 · DOI
  34. 10.1145/3544548.3581405 · DOI
  35. Gerben J. Westerhof and Ernst T. Bohlmeijer. 2014. Celebrating fifty years of research and applications in reminiscence and life review: State of the art and new directions. Journal of Aging Studies 29 (April 2014) 107–114. 10.1016/j.jaging.2014.02.003 · DOI
  36. Shuai Yang Yuying Ge Yang Li Yukang Chen Yixiao Ge Ying Shan and Yingcong Chen. 2024. SEED-Story: Multimodal Long Story Generation with Large Language Model. arxiv:https://arXiv.org/abs/2407.08683 [cs.CV] https://arxiv.org/abs/2407.08683 · arXiv
  37. Shukang Yin Chaoyou Fu Sirui Zhao Ke Li Xing Sun Tong Xu and Enhong Chen. 2024. A Survey on Multimodal Large Language Models. arxiv:https://arXiv.org/abs/2306.13549 [cs.CV] https://arxiv.org/abs/2306.13549 · arXiv
  38. Chuanqi Zang Jiji Tang Rongsheng Zhang Zeng Zhao Tangjie Lv Mingtao Pei and Wei Liang. 2024. Let Storytelling Tell Vivid Stories: An Expressive and Fluent Multimodal Storyteller. arxiv:https://arXiv.org/abs/2403.07301 [cs.CV] https://arxiv.org/abs/2403.07301 · arXiv
  39. 10.1145/3613904.3642545 · DOI
  40. Zhongyue Zhang Lina Xu Xingkai Wang Xu Zhang and Mingming Fan. 2025. Understanding and Co-designing Photo-based Reminiscence with Older Adults. Proc. ACM Hum.-Comput. Interact. 9 2 Article CSCW196 (April 2025) 30 pages. 10.1145/3711094 · DOI
  41. 10.1145/3491102.3501855 · DOI

Metadata

Authors
Sun, J., Zhang, Z., Wang, M., Li, N., Lu, Z., Xiang, Y., Zhang, L., Zhang, Y., Wang, Q., & Fan, M.
Affiliations
  • Lenovo Research, Beijing, China
  • The Hong Kong University of Science and Technology (Guangzhou), Guangzhou, China
  • Southeast University, Nanjing, China and Lenovo Research, Beijing, China
  • The Hong Kong University of Science and Technology (Guangzhou), Guangzhou, China and The Hong Kong University of Science and Technology, Hong Kong, China
Venue
Proceedings of the 2025 CHI Conference on Human Factors in Computing Systems
Publisher
ACM
Published
2025-04-25
Pages
1-22
Cited by
12
References
9

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review