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Aligning video generation models to human intent and physical constraints is significantly harder than for text or images, necessitating a diverse suite of post-training techniques beyond simple fine-tuning.
By integrating fresh and delayed signals, this approach boosts viewer engagement and revenue while reducing model complexity by nearly 42%.
