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dOPSD leverages a model's own decoding process to provide on-policy supervision, leading to substantial gains in reasoning performance without external labels.
Flex-Forcing achieves superior video generation quality and stability by unifying autoregressive and bidirectional methods, all while speeding up inference.
dMoE slashes the memory footprint of Mixture-of-Experts Diffusion LLMs by up to 80% without sacrificing performance, finally making them practical.
Naively quantizing autoregressive video diffusion models tanks performance due to exponentially increasing error accumulation across frames and heterogeneous outlier patterns, but Q-ARVD solves it.
