Design space exploration (DSE) for Text-to-Image (TTI) models entails navigating a vast, opaque space of possible image outputs, through a commensurately vast input space of hyperparameters and prompt text. Minor adjustments to prompt input can surface unexpectedly disparate images. How can interfaces support end-users in reliably steering prompt-space explorations towards interesting results? Our design probe, DreamSheets, supports exploration strategies with LLM-based functions for assisted prompt construction and simultaneous display of generated results, hosted in a spreadsheet interface. The flexible layout and novel generative functions enable experimentation with user-defined workflows. Two studies, a preliminary lab study and a longitudinal study with five expert artists, revealed a set of strategies participants use to tackle the challenges of TTI design space exploration, and the interface features required to support them - like using text-generation to define local "axes" of exploration. We distill these insights into a UI mockup to guide future interfaces.
@article{arxiv.2310.09985,
title = {Prompting for Discovery: Flexible Sense-Making for AI Art-Making with Dreamsheets},
author = {Shm Garanganao Almeda and J. D. Zamfirescu-Pereira and Kyu Won Kim and Pradeep Mani Rathnam and Bjoern Hartmann},
journal= {arXiv preprint arXiv:2310.09985},
year = {2024}
}