On-the-fly Repulsion in the Contextual Space for Rich Diversity in Diffusion Transformers

1. 1Identify the typicality bias in current text-to-image diffusion models
2. 2Modify the model to incorporate on-the-fly repulsion in the contextual space
3. 3Implement the modified model to generate more diverse images
4. 4Evaluate the performance of the modified model using metrics such as visual variety and semantic alignment

AI engineers and researchers working on text-to-image models can benefit from this approach to improve the diversity of generated images, while product managers can leverage this technology to develop more creative applications

💡 On-the-fly repulsion in contextual space can improve the diversity of generated images in diffusion transformers

💡 Boost diversity in text-to-image generation with on-the-fly repulsion in contextual space!