Composable Prompting Workspaces for Creative Writing: Exploration and Iteration Using Dynamic Widgets
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Abstract (arXiv)
Generative AI models offer many possibilities for text creation and transformation. Current graphical user interfaces (GUIs) for prompting them lack support for iterative exploration, as they do not represent prompts as actionable interface objects. We propose the concept of a composable prompting canvas for text exploration and iteration using dynamic widgets. Users generate widgets through system suggestions, prompting, or manually to capture task-relevant facets that affect the generated text. In a comparative study with a baseline (conversational UI), 18 participants worked on two writing tasks, creating diverse prompting environments with custom widgets and spatial layouts. They reported having more control over the generated text and preferred our system over the baseline. Our design significantly outperformed the baseline on the Creativity Support Index, and participants felt the results were worth the effort. This work highlights the need for GUIs that support user-driven customization and (re-)structuring to increase both the flexibility and efficiency of prompting.
Key facts. Cited by 3 papers in the map (data through 14 Oct 2026). Builds on 21 of its 43 references that are in the map. First posted on arXiv 27 Mar 2025.
Builds on
21 of 43 references.
References · 21
- 2021Program Synthesis with Large Language Modelscited by 3,637
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- 2023Choice Over Control: How Users Write with Large Language Models using Diegetic and Non-Diegetic Promptingcited by 36
9 more
- 2023Writer-Defined AI Personas for On-Demand Feedback Generationcited by 36
- 2023DirectGPT: A Direct Manipulation Interface to Interact with Large Language Modelscited by 32
- 2023Spellburst: A Node-based Interface for Exploratory Creative Coding with Natural Language Promptscited by 30
- 2021Adapting User Interfaces with Model-based Reinforcement Learningcited by 17
- 2022CodeToon: Story Ideation, Auto Comic Generation, and Structure Mapping for Code-Driven Storytellingcited by 14
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- 2024The Dearth of the Author in AI-Supported Writingcited by 10
- 2024Automatic Histograms: Leveraging Language Models for Text Dataset Explorationcited by 8
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Citing papers per year: 2025: 1; 2026: 2.
3 papers.