EvolvED: Evolutionary Embeddings to Understand the Generation Process of Diffusion Models

Understand

Diffusion models, widely used in image generation, rely on iterative refinement to generate images from noise.

• Understanding this data evolution is important for model development and interpretability, yet challenging due to its high-dimensional, iterative nature.
• Prior works often focus on static or instance-level analyses, missing the iterative and holistic aspects of the generative path.
• While dimensionality reduction can visualize image evolution for few instances, it does preserve the iterative structure.