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Memory overload in autoregressive video generation can be tackled by absorbing historical context into model weights, achieving up to 50% cache reduction with minimal quality loss.
ICMPG achieves a groundbreaking balance between semantic fidelity and physical realism in motion synthesis, outperforming traditional methods in both standard and zero-shot scenarios.
Autoregressive video models can now generate 4-minute videos without retraining, thanks to a clever inference-time hack that fixes positional embedding bias and injects dynamic priors.
