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CrossDistill: Balancing Quality and Diversity via Trajectory-Level Hybrid Few-Step Distillation

arXiv · AI, language, vision and robotics · article · Sep 13, 2026 · UTC

Few-step distillation accelerates diffusion models but must balance diversity and fidelity: trajectory-based distillation preserves mode coverage, while distribution matching sharpens samples but can reduce diversity. We show that this tension can be exploited in a noise-regime-dependent way: high-noise steps largely determine global modes, whereas low-noise steps refine local details. We propose CrossDistill, a trajectory-level hybrid distillation framework that splits the sampling trajectory at a crossover point, applies a trajectory-preserving objective on the high-noise interval and a dist

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