Abstract:We introduce Memento, a conversational AR assistant that permanently captures and memorizes user's verbal queries alongside their spatiotemporal and activity contexts. By storing these "memories," Memento discovers connections between users' recurring interests and the contexts that trigger them. Upon detection of similar or identical spatiotemporal activity, Memento proactively recalls user interests and delivers up-to-date responses through AR, seamlessly integrating AR experience into their daily routine. Unlike prior work, each interaction in Memento is not a transient event, but a connected series of interactions with coherent long--term perspective, tailored to the user's broader multimodal (visual, spatial, temporal, and embodied) context. We conduct a preliminary evaluation through user feedbacks with participants of diverse expertise in immersive apps, and explore the value of proactive context-aware AR assistant in everyday settings. We share our findings and challenges in designing a proactive, context-aware AR system.
| Comments: | 8 pages, 5 figures. This is the author's version of the article that appeared at the IEEE Conference on Virtual Reality and 3D User Interfaces Abstracts and Workshops (IEEE VRW) 2026 |
| Subjects: | Human-Computer Interaction (cs.HC); Computation and Language (cs.CL); Information Retrieval (cs.IR) |
| Cite as: | arXiv:2601.17622 [cs.HC] |
| (or arXiv:2601.17622v4 [cs.HC] for this version) | |
| https://doi.org/10.48550/arXiv.2601.17622 arXiv-issued DOI via DataCite |
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| Related DOI: | https://doi.org/10.1109/VRW70859.2026.00180
DOI(s) linking to related resources |
Submission history
From: Yoonsang Kim [view email]
[v1]
Sat, 24 Jan 2026 22:56:50 UTC (34,366 KB)
[v2]
Tue, 27 Jan 2026 03:30:01 UTC (34,366 KB)
[v3]
Sat, 31 Jan 2026 01:46:44 UTC (3,388 KB)
[v4]
Wed, 6 May 2026 21:23:50 UTC (3,388 KB)