The rapid progress of text-to-image (T2I) diffusion models has made it possible to generate highly detailed and accurate images from text inputs. However, as the length of the input text increases, current encoding methods, such as CLIP (Contrastive Language-Image Pretraining), encounter various limitations. These methods struggle to capture the full complexity of long text descriptions,…

Large Language Models (LLMs) have demonstrated remarkable progress in natural language processing tasks, inspiring researchers to explore similar approaches for text-to-image synthesis. At the same time, diffusion models have become the dominant approach in visual generation. However, the operational differences between the two approaches present a significant challenge in developing a unified methodology for language…