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Uncertainty-guided feedback can dramatically improve the reliability of reward models in visual diffusion, leading to superior optimization and quality outcomes.
CineWeaver breaks the mold by enabling long-form, reference-controllable, and multi-shot video generation without the need for retraining, setting a new standard in cinematic storytelling.
MMOE achieves faster convergence and superior generation quality in diffusion transformers by effectively integrating expert routing strategies, challenging the notion that more parameters always lead to better performance.
