PosterMate: Audience-driven Collaborative Persona Agents for Poster Design
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arXiv
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| Autori principali: | , , , |
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| Natura: | Preprint |
| Pubblicazione: |
2025
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| _version_ | 1866915408387244032 |
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| author | Shin, Donghoon Lee, Daniel Hsieh, Gary Chan, Gromit Yeuk-Yin |
| author_facet | Shin, Donghoon Lee, Daniel Hsieh, Gary Chan, Gromit Yeuk-Yin |
| contents | Poster designing can benefit from synchronous feedback from target audiences. However, gathering audiences with diverse perspectives and reconciling them on design edits can be challenging. Recent generative AI models present opportunities to simulate human-like interactions, but it is unclear how they may be used for feedback processes in design. We introduce PosterMate, a poster design assistant that facilitates collaboration by creating audience-driven persona agents constructed from marketing documents. PosterMate gathers feedback from each persona agent regarding poster components, and stimulates discussion with the help of a moderator to reach a conclusion. These agreed-upon edits can then be directly integrated into the poster design. Through our user study (N=12), we identified the potential of PosterMate to capture overlooked viewpoints, while serving as an effective prototyping tool. Additionally, our controlled online evaluation (N=100) revealed that the feedback from an individual persona agent is appropriate given its persona identity, and the discussion effectively synthesizes the different persona agents' perspectives. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2507_18572 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | PosterMate: Audience-driven Collaborative Persona Agents for Poster Design Shin, Donghoon Lee, Daniel Hsieh, Gary Chan, Gromit Yeuk-Yin Human-Computer Interaction Artificial Intelligence Computation and Language H.5.2; I.2.7 Poster designing can benefit from synchronous feedback from target audiences. However, gathering audiences with diverse perspectives and reconciling them on design edits can be challenging. Recent generative AI models present opportunities to simulate human-like interactions, but it is unclear how they may be used for feedback processes in design. We introduce PosterMate, a poster design assistant that facilitates collaboration by creating audience-driven persona agents constructed from marketing documents. PosterMate gathers feedback from each persona agent regarding poster components, and stimulates discussion with the help of a moderator to reach a conclusion. These agreed-upon edits can then be directly integrated into the poster design. Through our user study (N=12), we identified the potential of PosterMate to capture overlooked viewpoints, while serving as an effective prototyping tool. Additionally, our controlled online evaluation (N=100) revealed that the feedback from an individual persona agent is appropriate given its persona identity, and the discussion effectively synthesizes the different persona agents' perspectives. |
| title | PosterMate: Audience-driven Collaborative Persona Agents for Poster Design |
| topic | Human-Computer Interaction Artificial Intelligence Computation and Language H.5.2; I.2.7 |
| url | https://arxiv.org/abs/2507.18572 |