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This paper introduces LC-GRPO, a flow-based GRPO framework with Langevin correction that bridges the train-inference gap by aligning stochastic training rollouts with deterministic ODE sampling, improving reward optimization on models like SD3.5, FLUX.1-Dev, and HunyuanVideo.