PromptCrafter: Crafting Text-to-Image Prompt through Mixed-Initiative Dialogue with LLM

Hyerin Im; Jiseung Ryu; Juhyeong Park; Seungho Baek; Takyeon Lee

PromptCrafter: Crafting Text-to-Image Prompt through Mixed-Initiative Dialogue with LLM

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arxiv 2307.08985 v1 pith:LQSPNCQX submitted 2023-07-18 cs.HC cs.AI

Seungho Baek , Hyerin Im , Jiseung Ryu , Juhyeong Park , Takyeon Lee This is my paper · ORCID

classification cs.HCcs.AI

keywords usersmodelpromptcrafterprompttext-to-imagecapabilitycraftingefficiently

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Text-to-image generation model is able to generate images across a diverse range of subjects and styles based on a single prompt. Recent works have proposed a variety of interaction methods that help users understand the capabilities of models and utilize them. However, how to support users to efficiently explore the model's capability and to create effective prompts are still open-ended research questions. In this paper, we present PromptCrafter, a novel mixed-initiative system that allows step-by-step crafting of text-to-image prompt. Through the iterative process, users can efficiently explore the model's capability, and clarify their intent. PromptCrafter also supports users to refine prompts by answering various responses to clarifying questions generated by a Large Language Model. Lastly, users can revert to a desired step by reviewing the work history. In this workshop paper, we discuss the design process of PromptCrafter and our plans for follow-up studies.

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