Pith. sign in

REVIEW 2 cited by

A Taxonomy of Prompt Modifiers for Text-To-Image Generation

Not yet reviewed by Pith; the record is open.

This paper has not been read by Pith yet. Machine review is queued; the pith claim, tier, and objections will appear here once it completes.

SPECIMEN: schema-true, not a live event

T0 review · schema-true

One-sentence machine reading of the paper's core claim.

pith:XXXXXXXX · record.json · timestamp

arxiv 2204.13988 v3 pith:QFZQKIRQ submitted 2022-04-20 cs.MM cs.CLcs.HC

classification cs.MMcs.CLcs.HC
keywords promptgenerationtext-to-imagemodifiersgeneratedpracticeengineeringimages
verification ladder T0 review T1 audit T2 compute T3 formal

Signed reviews

No signed human review yet.

0 comments
read the original abstract

Text-to-image generation has seen an explosion of interest since 2021. Today, beautiful and intriguing digital images and artworks can be synthesized from textual inputs ("prompts") with deep generative models. Online communities around text-to-image generation and AI generated art have quickly emerged. This paper identifies six types of prompt modifiers used by practitioners in the online 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 text-to-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." We 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.

Discussion (0). Continue with ORCID to comment.

Forward citations

Cited by 2 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. Sketchar: Supporting Character Design and Illustration Prototyping Using Generative AI

    cs.HC 2025-08 conditional novelty 6.0 of 10

    Sketchar, a ChatGPT and DALL-E based prototyping tool, helped game designers without artistic backgrounds generate reference images and character documents that they rated as more supportive of creativity than sketchi...

  2. Sel3DCraft: Interactive Visual Prompts for User-Friendly Text-to-3D Generation

    cs.GR 2025-08 unverdicted novelty 4.0 of 10

    A visual prompt engineering system for text-to-3D generation uses multi-view MLLM scoring and interactive visualizations to help designers create models faster, with 70.5% time reduction and higher quality ratings (4....

Pith tools