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Achieving competitive video generation performance with under 1% of the trainable parameters typically needed could revolutionize how we approach fine-tuning in large-scale models.
OPSD-V shows that incorporating real video context during training can dramatically enhance the performance of autoregressive video generators, leading to superior visual quality and motion fidelity.
