A new paper from Google AI Research analyzes how diffusion models generate creative outputs. The study decomposes the sampling process to identify where novelty emerges versus where the model mimics training data. This technical deep-dive helps researchers control output diversity. It offers a framework to reduce repetitive patterns in generative vision systems.