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November 28, 2023Behaviour and Information Technology198 citationsOpen Access

A taxonomy of prompt modifiers for text-to-image generation

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JOJonas Oppenlaender

Key Points

  • This paper aims to classify types of prompt modifiers used in text-to-image generation and explore their implications.
  • Conducted a 3-month ethnographic study in online text-to-image communities.
  • Identified six types of prompt modifiers used by practitioners.
  • Discussed the application of prompt modifiers in prompt engineering.
  • A novel taxonomy of six prompt modifiers was developed.
  • The taxonomy serves as a foundation for future research in text-to-image generation.
  • It highlights broader implications for human-AI interaction beyond current applications.

Abstract

Text-guided synthesis of images has become enormously popular and online communities dedicated to text-to-image generation and art generated with Artificial Intelligence (AI) have emerged.While deep generative models can synthesise high-quality images and artworks from simple descriptive text prompts, practitioners of text-to-image generation typically seek to control the generative model's output by adding short key phrases ('modifiers') to the prompt.This paper identifies six types of prompt modifiers used by practitioners in the online text-toimage community based on a 3-month ethnographic study.The novel taxonomy of prompt modifiers provides researchers a conceptual starting point for investigating the practice of textto-image generation, but may also help practitioners of AI generated art improve their images.We further outline how prompt modifiers are applied in the practice of 'prompt engineering.' and discuss research opportunities of this novel creative practice in the field of Human-Computer Interaction (HCI).The paper concludes with a discussion of broader implications of prompt engineering from the perspective of Human-AI Interaction (HAI) in future applications beyond the use case of text-to-image generation and AI generated art.

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Cite This Study

Jonas Oppenlaender (2023) studied this question.

synapsesocial.com/papers/6a03acb2d2f86d5a82f01649https://doi.org/10.1080/0144929x.2023.2286532
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