Record link: 
http://hdl.handle.net/20.500.12708/225024
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Title: 
PromptMap: An Alternative Interaction Style for AI-Based Image Generation
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Citation: 
Adamkiewicz, K., Woźniak, P. W., Dominiak, J., Romanowski, A., Karolus, J., & Frolov, S. (2025). PromptMap: An Alternative Interaction Style for AI-Based Image Generation. In T. Li, F. Paternò, & K. Väänänen (Eds.), IUI ’25: Proceedings of the 30th International Conference on Intelligent User Interfaces (pp. 1162–1176). Association for Computing Machinery. https://doi.org/10.1145/3708359.3712150
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Publisher DOI: 
10.1145/3708359.3712150
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Publication Type: 
Inproceedings - Full-Paper Contribution
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Language: 
English
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Authors: 
Adamkiewicz, Krzysztof 
Woźniak, Paweł W. 
Dominiak, Julia 
Romanowski, Andrzej 
Karolus, Jakob 
Frolov, Stanislav 
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Organisational Unit: 
E193-05 - Forschungsbereich Human Computer Interaction 
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Published in: 
IUI '25: Proceedings of the 30th International Conference on Intelligent User Interfaces 
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ISBN: 
979-8-4007-1306-4
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Date (published): 
24-Mar-2025
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Event name: 
IUI '25: 30th International Conference on Intelligent User Interfaces 
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Event date: 
24-Mar-2025 - 27-Mar-2025
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Event place: 
Cagliari, Italy
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Number of Pages: 
15
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Publisher: 
Association for Computing Machinery
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Peer reviewed: 
Yes
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Keywords: 
Generative AI; image generation; interaction methods
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Abstract: 
Recent technological advances popularized the use of image generation among the general public. Crafting effective prompts can, however, be difficult for novice users. To tackle this challenge, we developed PromptMap, a new interaction style for text-to-image AI that allows users to freely explore a vast collection of synthetic prompts through a map-like view with semantic zoom. PromptMap groups images visually by their semantic similarity, allowing users to discover relevant examples. We evaluated PromptMap in a between-subject online study (n = 60) and a qualitative within-subject study (n = 12). We found that PromptMap supported users in crafting prompts by providing them with examples. We also demonstrated the feasibility of using LLMs to create vast example collections. Our work contributes a new interaction style that supports users unfamiliar with prompting in achieving a satisfactory image output.
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Research Areas: 
Visual Computing and Human-Centered Technology: 100%
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Science Branch: 
1020 - Informatik: 90%
1010 - Mathematik: 10%
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Appears in Collections:
Conference Paper

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