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Latent Reward Registers enable real-time preference alignment in diffusion models, achieving up to 33x reduction in computational costs while enhancing accuracy and perceptual quality.
Stop handcuffing student diffusion models to their teachers: framing distribution matching as a reward unlocks more stable and performant distillation via RL techniques.
