Pith. sign in

REVIEW

Prompting for Discovery: Flexible Sense-Making for AI Art-Making with Dreamsheets

Not yet reviewed by Pith; the record is open.

This paper has not been read by Pith yet. Machine review is queued; the pith claim, tier, and objections will appear here once it completes.

SPECIMEN: schema-true, not a live event

T0 review · schema-true

One-sentence machine reading of the paper's core claim.

pith:XXXXXXXX · record.json · timestamp

arxiv 2310.09985 v2 pith:OLTXZNUM submitted 2023-10-15 cs.HC

classification cs.HC
keywords explorationspacedesignpromptdreamsheetsflexiblefunctionsinput
verification ladder T0 review T1 audit T2 compute T3 formal

Signed reviews

No signed human review yet.

0 comments
read the original abstract

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.

Discussion (0). Continue with ORCID to comment.

Pith tools