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DeckFlow: A Card Game Interface for Exploring Generative Model Flows

Published: 29 October 2023 Publication History

Abstract

Recent Generative AI models have been shown to be substantially useful in different fields, often bridging modal gaps, such as text-prompted image or human motion generation. However, their accompanying interfaces do not sufficiently support iteration and interaction between models, and due to the computational intensity of generative technology, can be unforgiving to user errors and missteps. We propose DeckFlow, a no-code interface for multimodal generative workflows which encourages rapid iteration and experimentation between disparate models. DeckFlow emphasizes the persistence of output, the maintenance of generation settings and dependencies, and continual steering through user-defined concept groups. Taking design cues from Card Games and Affinity Diagrams, DeckFlow is aimed to lower the barrier for non-experts to explore and interact with generative AI.

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References

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Cited By

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  • (2024)Multimodal Outputs for the Workplace From Generative AIComputational Practices and Applications for Digital Art and Crafting10.4018/979-8-3693-2927-6.ch008(198-225)Online publication date: 17-Jul-2024

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  1. DeckFlow: A Card Game Interface for Exploring Generative Model Flows

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    Published In

    cover image ACM Conferences
    UIST '23 Adjunct: Adjunct Proceedings of the 36th Annual ACM Symposium on User Interface Software and Technology
    October 2023
    424 pages
    ISBN:9798400700965
    DOI:10.1145/3586182
    Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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    New York, NY, United States

    Publication History

    Published: 29 October 2023

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    Author Tags

    1. generative model
    2. multimodal interaction
    3. text-to-image generation

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    UIST '23

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    Overall Acceptance Rate 355 of 1,733 submissions, 20%

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    • (2024)Multimodal Outputs for the Workplace From Generative AIComputational Practices and Applications for Digital Art and Crafting10.4018/979-8-3693-2927-6.ch008(198-225)Online publication date: 17-Jul-2024

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