Equilibrium Forcing: video generators that adapt inference per sample for long horizons
du_yilun · x · 2026-08-19
Researchers introduce Equilibrium Forcing (EqF), extending Equilibrium Matching (EqM). Motivation: rigid, hand-designed sampling schedules become inaccurate during autoregressive video generation as errors accumulate. EqF removes noise-level conditioning to let the generator adapt its inference procedure to the sample being generated, enabling budget-adaptive sampling and improving long-horizon video generation.
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