Abstract
Conditional generative models such as DALL-E and Stable Diffusion generate images based on a user-defined text, the prompt. Finding and refining prompts that produce a desired image has become the art of prompt engineering. Generative models do not provide a built-in retrieval model for a user's information need expressed through prompts. In light of an extensive literature review, we reframe prompt engineering for generative models as interactive text-based retrieval on a novel kind of "infinite index". We apply these insights for the first time in a case study on image generation for game design with an expert. Finally, we envision how active learning may help to guide the retrieval of generated images.
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Deckers, N., Fröbe, M., Kiesel, J., Pandolfo, G., Schröder, C., Stein, B., & Potthast, M. (2023). The Infinite Index: Information Retrieval on Generative Text-To-Image Models. In CHIIR 2023 - Proceedings of the 2023 Conference on Human Information Interaction and Retrieval (pp. 172–186). Association for Computing Machinery, Inc. https://doi.org/10.1145/3576840.3578327
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