%0 Journal Article %1 Deckers2022-pr %A Deckers, Niklas %A Fröbe, Maik %A Kiesel, Johannes %A Pandolfo, Gianluca %A Schröder, Christopher %A Stein, Benno %A Potthast, Martin %D 2022 %I arXiv %K %T The infinite index: Information retrieval on generative text-to-image models %X 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.

@article{Deckers2022-pr, 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.}, added-at = {2024-09-10T10:41:24.000+0200}, author = {Deckers, Niklas and Fr{\"o}be, Maik and Kiesel, Johannes and Pandolfo, Gianluca and Schr{\"o}der, Christopher and Stein, Benno and Potthast, Martin}, biburl = {https://puma.scadsai.uni-leipzig.de/bibtex/2456a7c36606519aad166f49b39cc6581/scadsfct}, interhash = {c037ab5acc187f278c23f845035652fa}, intrahash = {456a7c36606519aad166f49b39cc6581}, keywords = {}, publisher = {arXiv}, timestamp = {2024-09-10T10:47:32.000+0200}, title = {The infinite index: Information retrieval on generative text-to-image models}, year = 2022 }