  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.

Human-Computer Interaction;Artificial Intelligence