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CausVid: bidirectional-teacher to causal-video-student distillation

Contribution grade

Streaming generative models · Human-designed research method or resource

Reference score65,000Provisional editorial estimate of this exact contribution; its grade is assessed separately.

What changed

Initialized a causal video student from teacher ODE trajectories and applied asymmetric distribution-matching distillation for few-step cached streaming generation.

Scientific scope

Initialized a causal video student from teacher ODE trajectories and applied asymmetric distribution-matching distillation for few-step cached streaming generation. Inherits DMD and causal/autoregressive video modeling. Reduced empirical error accumulation is not an indefinite-stability or physical-accuracy theorem. Latency/FPS are original hardware/model measurements, not current universal rankings.

Evidence

The linked original sources describe the stated contribution and its evidence limits. WRS has not independently rerun the experiments or certified a proof. Inherits DMD and causal/autoregressive video modeling. Reduced empirical error accumulation is not an indefinite-stability or physical-accuracy theorem. Latency/FPS are original hardware/model measurements, not current universal rankings.

Contributors

Provisional WRS assessment, edition 2026-10-16.1. Independent expert calibration is pending. This grade does not certify correctness or assign ownership.

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