We introduce a new ''rule'' for understanding diffusion models: Selective Underfitting.
It explains:
馃毃 How diffusion models generalize beyond training data
馃毃 Why popular training recipes (e.g., DiT, REPA) are effective and scale well
Co-led with @kiwhansong0!
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