2026-05-10T08:04:24.048Z http://ezaposleni.singidunum.ac.rs/rest/sciNaucniRezultati/oai

ezaposleni.singidunum.ac.rs/rest/sciNaucniRezultati/oai:1:9718 2023-12-22T21:53:24Z 1

Bias Analysis in Stable Diffusion and MidJourney Models 2023 http://ezaposleni.singidunum.ac.rs/rest/sciNaucniRezultati/oai/record/1/9718 https://link.springer.com/chapter/10.1007/978-3-031-35081-8_32 Л. Аничин M. Stojmenović In recent months, all kinds of image-generating models got the spot-light, opening many possibilities for further research direction, and from the commercial side, many teams will be able to start experimenting and building products on top of them. A sub-area of image generation that picked the most interest in the eye of the public is text-to-image models, most notably Stable Diffusion and MidJourney. Open sourcing Stable Diffusion and free tier of MidJourney allowed many product teams to start building on top of them with little to no resources. However, applying any pre-trained model without proper testing and experimentation creates unknown risks for companies and teams using them. In this paper, we are demonstrating what might happen if such models are used without additional filtering and testing through bias detection. conferenceObject 378 388 Intelligent Systems and Machine Learning