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DTSTART;TZID=America/New_York:20220503T091500
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DTSTAMP:20260421T100845
CREATED:20220422T095003Z
LAST-MODIFIED:20220426T150437Z
UID:1737-1651569300-1651570200@www.germanhci.de
SUMMARY:GANSlider: How Users Control Generative Models for Images using Multiple Sliders with and without Feedforward Information
DESCRIPTION:We investigate how multiple sliders with and without feedforward visualizations influence users’ control of generative models. In an online study (N=138)\, we collected a dataset of people interacting with a generative adversarial network (StyleGAN2) in an image reconstruction task. We found that more control dimensions (sliders) significantly increase task difficulty and user actions. Visual feedforward partly mitigates this by enabling more goal-directed interaction. However\, we found no evidence of faster or more accurate task performance. This indicates a tradeoff between feedforward detail and implied cognitive costs\, such as attention. Moreover\, we found that visualizations alone are not always sufficient for users to understand individual control dimensions. Our study quantifies fundamental UI design factors and resulting interaction behavior in this context\, revealing opportunities for improvement in the UI design for interactive applications of generative models. We close by discussing design directions and further aspects.
URL:https://www.germanhci.de/event/ganslider-how-users-control-generative-models-for-images-using-multiple-sliders-with-and-without-feedforward-information/
LOCATION:Room: 394
CATEGORIES:Trust and Control in AI Systems
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