GatheringSense: AI-Generated Imagery and Embodied Experiences for Understanding Literati Gatherings
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arXiv
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| Autori principali: | , , , , |
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| Natura: | Preprint |
| Pubblicazione: |
2026
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| _version_ | 1866915796387627008 |
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| author | Zhou, You Wang, Bingyuan Guo, Hongcheng Cao, Rui Wang, Zeyu |
| author_facet | Zhou, You Wang, Bingyuan Guo, Hongcheng Cao, Rui Wang, Zeyu |
| contents | Chinese literati gatherings (Wenren Yaji), as a situated form of Chinese traditional culture, remain underexplored in depth. Although generative AI supports powerful multimodal generation, current cultural applications largely emphasize aesthetic reproduction and struggle to convey the deeper meanings of cultural rituals and social frameworks. Based on embodied cognition, we propose an AI-driven dual-path framework for cultural understanding, which we instantiate through GatheringSense, a literati-gathering experience. We conduct a mixed-methods study (N=48) to compare how AI-generated multimodal content and embodied participation complement each other in supporting the understanding of literati gatherings and fostering cultural resonance. Our results show that AI-generated content effectively improves the readability of cultural symbols and initial emotional attraction, yet limitations in physical coherence and micro-level credibility may affect users' satisfaction. In contrast, embodied experience significantly deepens participants' understanding of ritual rules and social roles, and increases their psychological closeness and presence. Based on these findings, we offer empirical evidence and five transferable design implications for generative experience in cultural heritage. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2602_12565 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | GatheringSense: AI-Generated Imagery and Embodied Experiences for Understanding Literati Gatherings Zhou, You Wang, Bingyuan Guo, Hongcheng Cao, Rui Wang, Zeyu Human-Computer Interaction Chinese literati gatherings (Wenren Yaji), as a situated form of Chinese traditional culture, remain underexplored in depth. Although generative AI supports powerful multimodal generation, current cultural applications largely emphasize aesthetic reproduction and struggle to convey the deeper meanings of cultural rituals and social frameworks. Based on embodied cognition, we propose an AI-driven dual-path framework for cultural understanding, which we instantiate through GatheringSense, a literati-gathering experience. We conduct a mixed-methods study (N=48) to compare how AI-generated multimodal content and embodied participation complement each other in supporting the understanding of literati gatherings and fostering cultural resonance. Our results show that AI-generated content effectively improves the readability of cultural symbols and initial emotional attraction, yet limitations in physical coherence and micro-level credibility may affect users' satisfaction. In contrast, embodied experience significantly deepens participants' understanding of ritual rules and social roles, and increases their psychological closeness and presence. Based on these findings, we offer empirical evidence and five transferable design implications for generative experience in cultural heritage. |
| title | GatheringSense: AI-Generated Imagery and Embodied Experiences for Understanding Literati Gatherings |
| topic | Human-Computer Interaction |
| url | https://arxiv.org/abs/2602.12565 |