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PRIMFLOW: Learning Trajectory Primitives for Few-Step Distillation
Few-step trajectory distillation aims to learn accurate global updates from dense local supervision along a teacher's sampling trajectory. Existing approaches construct within-step dynamics using specific trajectory parameterizations or discrete interval predictions, tying the learned update to a pr
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