Closing the Domain Gap in Biomedical Imaging by In-Context Control Samples

ArXi:2604.20824v1 Announce Type: new The central problem in biomedical imaging are batch effects: systematic technical variations unrelated to the biological signal of interest. These batch effects critically undermine experimental reproducibility and are the primary cause of failure of deep learning systems on new experimental batches, preventing their practical use in the real world. Despite years of research, no method has succeeded in closing this performance gap for deep learning models.