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Representation Learning in Diffusion and Flow-based Model: An Application Aspect

arXiv · AI, language, vision and robotics · article · Aug 25, 2026 · UTC

Diffusion models and flow-based models have recently become the dominant paradigms in generative modeling, largely due to their ability to learn rich, multi-level visual representations through large-scale training. This creates a bidirectional relationship between generative models and representation learning: improving representation learning enhances generation quality, while the learned representations can be leveraged for broader understanding tasks. This survey systematically explores this interplay with a focus on applications. We propose a three-tier progressive framework that organize

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