Peeking Ahead of the Field Study: Exploring VLM Personas as Support Tools for Embodied Studies in HCI
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arXiv
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| Autores principales: | , , , , , , , , , , , |
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| Formato: | Preprint |
| Publicado: |
2026
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| Materias: | |
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| _version_ | 1866908839429799936 |
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| author | Gui, Xinyue Xia, Ding Colley, Mark Li, Yuan Chauhan, Vishal Anubhav, Anubhav Zhou, Zhongyi Javanmardi, Ehsan Seo, Stela Hanbyeol Chang, Chia-Ming Tsukada, Manabu Igarashi, Takeo |
| author_facet | Gui, Xinyue Xia, Ding Colley, Mark Li, Yuan Chauhan, Vishal Anubhav, Anubhav Zhou, Zhongyi Javanmardi, Ehsan Seo, Stela Hanbyeol Chang, Chia-Ming Tsukada, Manabu Igarashi, Takeo |
| contents | Field studies are irreplaceable but costly, time-consuming, and error-prone, which need careful preparation. Inspired by rapid-prototyping in manufacturing, we propose a fast, low-cost evaluation method using Vision-Language Model (VLM) personas to simulate outcomes comparable to field results. While LLMs show human-like reasoning and language capabilities, autonomous vehicle (AV)-pedestrian interaction requires spatial awareness, emotional empathy, and behavioral generation. This raises our research question: To what extent can VLM personas mimic human responses in field studies? We conducted parallel studies: 1) one real-world study with 20 participants, and 2) one video-study using 20 VLM personas, both on a street-crossing task. We compared their responses and interviewed five HCI researchers on potential applications. Results show that VLM personas mimic human response patterns (e.g., average crossing times of 5.25 s vs. 5.07 s) lack the behavioral variability and depth. They show promise for formative studies, field study preparation, and human data augmentation. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2602_16157 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | Peeking Ahead of the Field Study: Exploring VLM Personas as Support Tools for Embodied Studies in HCI Gui, Xinyue Xia, Ding Colley, Mark Li, Yuan Chauhan, Vishal Anubhav, Anubhav Zhou, Zhongyi Javanmardi, Ehsan Seo, Stela Hanbyeol Chang, Chia-Ming Tsukada, Manabu Igarashi, Takeo Human-Computer Interaction Field studies are irreplaceable but costly, time-consuming, and error-prone, which need careful preparation. Inspired by rapid-prototyping in manufacturing, we propose a fast, low-cost evaluation method using Vision-Language Model (VLM) personas to simulate outcomes comparable to field results. While LLMs show human-like reasoning and language capabilities, autonomous vehicle (AV)-pedestrian interaction requires spatial awareness, emotional empathy, and behavioral generation. This raises our research question: To what extent can VLM personas mimic human responses in field studies? We conducted parallel studies: 1) one real-world study with 20 participants, and 2) one video-study using 20 VLM personas, both on a street-crossing task. We compared their responses and interviewed five HCI researchers on potential applications. Results show that VLM personas mimic human response patterns (e.g., average crossing times of 5.25 s vs. 5.07 s) lack the behavioral variability and depth. They show promise for formative studies, field study preparation, and human data augmentation. |
| title | Peeking Ahead of the Field Study: Exploring VLM Personas as Support Tools for Embodied Studies in HCI |
| topic | Human-Computer Interaction |
| url | https://arxiv.org/abs/2602.16157 |