Memento: Towards Proactive Visualization of Everyday Memories with Personal Wearable AR Assistant
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arXiv
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| Autores principales: | , , |
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| Formato: | Preprint |
| Publicado: |
2026
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| Acceso en línea: | |
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| _version_ | 1866913096363147264 |
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| author | Kim, Yoonsang Yang, Yalong Kaufman, Arie E. |
| author_facet | Kim, Yoonsang Yang, Yalong Kaufman, Arie E. |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2601_17622 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | Memento: Towards Proactive Visualization of Everyday Memories with Personal Wearable AR Assistant Kim, Yoonsang Yang, Yalong Kaufman, Arie E. Human-Computer Interaction Computation and Language Information Retrieval 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. |
| title | Memento: Towards Proactive Visualization of Everyday Memories with Personal Wearable AR Assistant |
| topic | Human-Computer Interaction Computation and Language Information Retrieval |
| url | https://arxiv.org/abs/2601.17622 |