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- W4313706656 abstract "Generative text-to-image models (as exemplified by DALL-E, MidJourney, and Stable Diffusion) have recently made enormous technological leaps, demonstrating impressive results in many graphical domains—from logo design to digital painting and photographic composition. However, the quality of these results has led to existential crises in some fields of art, leading to questions about the role of human agency in the production of meaning in a graphical context. Such issues are central to visualization, and while these generative models have yet to be widely applied to visualization, it seems only a matter of time until their integration is manifest. Seeking to circumvent similar ponderous dilemmas, we attempt to understand the roles that generative models might play across visualization. We do so by constructing a framework that characterizes what these technologies offer at various stages of the visualization workflow, augmented and analyzed through semi-structured interviews with 21 experts from related domains. Throughthis work, we map the space of opportunities and risks that might arise in this intersection, identifying doomsday prophecies and delicious low-hanging fruits that are ripe for research." @default.
- W4313706656 created "2023-01-08" @default.
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- W4313706656 date "2023-01-07" @default.
- W4313706656 modified "2023-09-27" @default.
- W4313706656 title "Doom or Deliciousness: Challenges and Opportunities for Visualization in the Age of Generative Models" @default.
- W4313706656 doi "https://doi.org/10.31219/osf.io/3jrcm" @default.
- W4313706656 hasPublicationYear "2023" @default.
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