Most generative models learn V-shaped flows—each sample travels alone from prior to data along its own near-straight path.
Effective, but blind to the fact that real data has hierarchical structure.
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Models learn a shared representation path before specializing
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Better captures hierarchical relationships in data
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More efficient use of model capacity
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Natural fit for data with common structure + individual variation
