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Promptify: Text-to-Image Generation through Interactive Prompt Exploration with Large Language Models

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arxiv 2304.09337 v1 pith:SWEKFMBY submitted 2023-04-18 cs.HC cs.AIcs.MM

classification cs.HCcs.AIcs.MM
keywords promptifypromptstext-to-imagemodelspromptuserusersexploration
verification ladder T0 review T1 audit T2 compute T3 formal

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Text-to-image generative models have demonstrated remarkable capabilities in generating high-quality images based on textual prompts. However, crafting prompts that accurately capture the user's creative intent remains challenging. It often involves laborious trial-and-error procedures to ensure that the model interprets the prompts in alignment with the user's intention. To address the challenges, we present Promptify, an interactive system that supports prompt exploration and refinement for text-to-image generative models. Promptify utilizes a suggestion engine powered by large language models to help users quickly explore and craft diverse prompts. Our interface allows users to organize the generated images flexibly, and based on their preferences, Promptify suggests potential changes to the original prompt. This feedback loop enables users to iteratively refine their prompts and enhance desired features while avoiding unwanted ones. Our user study shows that Promptify effectively facilitates the text-to-image workflow and outperforms an existing baseline tool widely used for text-to-image generation.

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Cited by 1 Pith paper

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. OpenAlex reports about 4 citations worldwide. Full citation record

  1. POET: Supporting Prompting Creativity and Personalization with Automated Expansion of Text-to-Image Generation

    cs.CV 2025-04 conditional novelty 6.0 of 10

    POET is a tool that finds hidden sameness in AI-generated images, widens those dimensions for more variety, and personalizes future outputs from user feedback.

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