PromptCrafter: Crafting Text-to-Image Prompt through Mixed-Initiative Dialogue with LLM
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Abstract (arXiv)
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.
Key facts. Cited by 6 papers in the map (data through 7 Oct 2026). Builds on 10 of its 16 references that are in the map. First posted on arXiv 18 Jul 2023.
Builds on
10 of 16 references.
References · 10
- 2020Language Models are Few-Shot Learnerscited by 32,199
- 2021High-Resolution Image Synthesis with Latent Diffusion Modelscited by 18,694
- 2022Chain-of-Thought Prompting Elicits Reasoning in Large Language Modelscited by 12,302
- 2022Hierarchical Text-Conditional Image Generation with CLIP Latentscited by 6,539
- 2021Zero-Shot Text-to-Image Generationcited by 4,276
- 2021Prompt Programming for Large Language Models: Beyond the Few-Shot Paradigmcited by 599
- 2021Design Guidelines for Prompt Engineering Text-to-Image Generative Modelscited by 216
- 20223DALL-E: Integrating Text-to-Image AI in 3D Design Workflowscited by 41
- 2022Opal: Multimodal Image Generation for News Illustrationcited by 36
- 2022HELP ME THINK: A Simple Prompting Strategy for Non-experts to Create Customized Content with Modelscited by 17
Built on by
Citing papers per year: 2024: 1; 2025: 2; 2026: 3.
6 papers.
- 2026Diffusion Probe: Generated Image Result Prediction Using CNN Probescited by 13
- 2024Growth Inhibitors for Suppressing Inappropriate Image Concepts in Diffusion Modelscited by 10
- 2025Expanding the Generative AI Design Space through Structured Prompting and Multimodal Interfacescited by 3
- 2026Say It My Way: Exploring Control in Conversational Visual Question Answering with Blind Userscited by 2
- 2026SceneCraft: Interactive System for Image Editing via Scene Graphcited by 1
- 2025Decoder-Only LLMs are Better Controllers for Diffusion Modelscited by 0
- 2026SceneCraft: Interactive System for Image Editing via Scene Graph15 Jun 2026
- 2026Diffusion Probe: Generated Image Result Prediction Using CNN Probes27 Feb 2026
- 2026Say It My Way: Exploring Control in Conversational Visual Question Answering with Blind Users18 Feb 2026
- 2025Expanding the Generative AI Design Space through Structured Prompting and Multimodal Interfaces19 Apr 2025
- 2025Decoder-Only LLMs are Better Controllers for Diffusion Models6 Feb 2025
- 2024Growth Inhibitors for Suppressing Inappropriate Image Concepts in Diffusion Models2 Aug 2024