Expandora: Broadening Design Exploration with Text-to-Image Model
arXiv:2503.00791 · doi:10.1145/3706599.3720189
Abstract
Broad exploration of references is critical in the visual design process. While text-to-image (T2I) models offer efficiency and customization of exploration, they often limit support for divergence in exploration. We conducted a formative study (N=6) to investigate the limitations of current interaction with the T2I model for broad exploration and found that designers struggle to articulate exploratory intentions and manage iterative, non-linear workflows. To address these challenges, we developed Expandora. Users can specify their exploratory intentions and desired diversity levels through structured input, and using an LLM-based pipeline, Expandora generates tailored prompt variations. The results are displayed in a mindmap-like interface that encourages non-linear workflows. A user study (N=8) demonstrated that Expandora significantly increases prompt diversity, the number of prompts users tried within a given time, and user satisfaction compared to the baseline. Nonetheless, its limitations in supporting convergent thinking suggest opportunities for holistically improving creative processes.
Accepted to CHI'25 LBW
References in corpus (5)
- Large-scale Text-to-Image Generation Models for Visual Artists' Creative Works
- The Effects of Generative AI on Design Fixation and Divergent Thinking
- Luminate: Structured Generation and Exploration of Design Space with Large Language Models for Human-AI Co-Creation
- PromptCharm: Text-to-Image Generation through Multi-modal Prompting and Refinement
- Prompting for products: Investigating design space exploration strategies for text-to-image generative models