Researchers propose an iterative process to improve generative modeling for image generation. They use flow matching, a technique that can lead to hallucinations - images that are unrealistic. The authors explain why this happens and suggest a way to correct it through gradual refinement. This approach can be integrated into various generative modeling techniques, enhancing their performance and robustness. --- Why it matters: This matters because current generative models often struggle with producing realistic images, leading to issues in applications like image synthesis for entertainment or inverse problems. The proposed iterative process could improve the reliability of these systems. Source: https://arxiv.org/abs/2502.16445