What is in a Text-to-Image Prompt: The Potential of Stable Diffusion in Visual Arts Education
Not on the map. Why?
Abstract (arXiv)
Text-to-Image artificial intelligence (AI) recently saw a major breakthrough with the release of Dall-E and its open-source counterpart, Stable Diffusion. These programs allow anyone to create original visual art pieces by simply providing descriptions in natural language (prompts). Using a sample of 72,980 Stable Diffusion prompts, we propose a formalization of this new medium of art creation and assess its potential for teaching the history of art, aesthetics, and technique. Our findings indicate that text-to-Image AI has the potential to revolutionize the way art is taught, offering new, cost-effective possibilities for experimentation and expression. However, it also raises important questions about the ownership of artistic works. As more and more art is created using these programs, it will be crucial to establish new legal and economic models to protect the rights of artists.
Key facts. Cited by 14 papers in the map (data through 7 Oct 2026). First posted on arXiv 5 Jan 2023.
Builds on
No reference list yet.
Built on by
Citing papers per year: 2023: 2; 2024: 5; 2025: 5; 2026: 2.
14 papers.
Sort:
By area:
- 2023In-Context Impersonation Reveals Large Language Models' Strengths and Biasescited by 154
- 2023Students' Voices on Generative AI: Perceptions, Benefits, and Challenges in Higher Educationcited by 41
- 2024A Survey on Quality Metrics for Text-to-Image Generationcited by 17
- 2024Training-free Composite Scene Generation for Layout-to-Image Synthesiscited by 11
- 2025RAPO++: Cross-Stage Prompt Optimization for Text-to-Video Generation via Data Alignment and Test-Time Scalingcited by 9
- 2024Charting the Future of AI in Project-Based Learning: A Co-Design Exploration with Studentscited by 8
- 2025PromptMap: An Alternative Interaction Style for AI-Based Image Generationcited by 8
- 2025Detail++: Training-Free Detail Enhancer for T2I Diffusion Modelscited by 4
- 2024Picturing Ambiguity: A Visual Twist on the Winograd Schema Challengecited by 3
- 2026PromptEvolver: Prompt Inversion through Evolutionary Optimization in Natural-Language Spacecited by 1
- 2024Melon Fruit Detection and Quality Assessment Using Generative AI-Based Image Data Augmentationcited by 0
- 2025Speaking images. A novel framework for the automated self-description of artworkscited by 0
- 2026Evolutionary Token-Level Prompt Optimization for Diffusion Models10 Apr 2026
- 2026PromptEvolver: Prompt Inversion through Evolutionary Optimization in Natural-Language Space3 Apr 2026
- 2025RAPO++: Cross-Stage Prompt Optimization for Text-to-Video Generation via Data Alignment and Test-Time Scaling23 Oct 2025
- 2025Thematic and Task-Based Categorization of K-12 GenAI Usages with Hierarchical Topic Modeling1 Aug 2025
- 2025Detail++: Training-Free Detail Enhancer for T2I Diffusion Models23 Jul 2025
- 2025Speaking images. A novel framework for the automated self-description of artworks28 May 2025
- 2025PromptMap: An Alternative Interaction Style for AI-Based Image Generation12 Mar 2025
- 2024Training-free Composite Scene Generation for Layout-to-Image Synthesis18 Jul 2024
- 2024Melon Fruit Detection and Quality Assessment Using Generative AI-Based Image Data Augmentation15 Jul 2024
- 2024Picturing Ambiguity: A Visual Twist on the Winograd Schema Challenge25 May 2024
- 2024A Survey on Quality Metrics for Text-to-Image Generation18 Mar 2024
- 2024Charting the Future of AI in Project-Based Learning: A Co-Design Exploration with Students26 Jan 2024
- 2023In-Context Impersonation Reveals Large Language Models' Strengths and Biasescited by 154
- 2023Students' Voices on Generative AI: Perceptions, Benefits, and Challenges in Higher Educationcited by 41
- 2024A Survey on Quality Metrics for Text-to-Image Generationcited by 17
- 2024Charting the Future of AI in Project-Based Learning: A Co-Design Exploration with Studentscited by 8
- 2025PromptMap: An Alternative Interaction Style for AI-Based Image Generationcited by 8
- 2024Picturing Ambiguity: A Visual Twist on the Winograd Schema Challengecited by 3
- 2026PromptEvolver: Prompt Inversion through Evolutionary Optimization in Natural-Language Spacecited by 1
- 2024Melon Fruit Detection and Quality Assessment Using Generative AI-Based Image Data Augmentationcited by 0
- 2025Speaking images. A novel framework for the automated self-description of artworkscited by 0
- 2025Thematic and Task-Based Categorization of K-12 GenAI Usages with Hierarchical Topic Modelingcited by 0
- 2026PromptEvolver: Prompt Inversion through Evolutionary Optimization in Natural-Language Space3 Apr 2026
- 2025Thematic and Task-Based Categorization of K-12 GenAI Usages with Hierarchical Topic Modeling1 Aug 2025
- 2025Speaking images. A novel framework for the automated self-description of artworks28 May 2025
- 2025PromptMap: An Alternative Interaction Style for AI-Based Image Generation12 Mar 2025
- 2024Melon Fruit Detection and Quality Assessment Using Generative AI-Based Image Data Augmentation15 Jul 2024
- 2024Picturing Ambiguity: A Visual Twist on the Winograd Schema Challenge25 May 2024
- 2024A Survey on Quality Metrics for Text-to-Image Generation18 Mar 2024
- 2024Charting the Future of AI in Project-Based Learning: A Co-Design Exploration with Students26 Jan 2024
- 2023In-Context Impersonation Reveals Large Language Models' Strengths and Biases24 May 2023
- 2023Students' Voices on Generative AI: Perceptions, Benefits, and Challenges in Higher Education29 Apr 2023