DRaFT fine-tunes diffusion models by differentiating through sampling to maximize rewards, outperforming RL baselines and improving aesthetics on Stable Diffusion 1.4.
Continuous control with deep reinforcement learning
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Directly Fine-Tuning Diffusion Models on Differentiable Rewards
DRaFT fine-tunes diffusion models by differentiating through sampling to maximize rewards, outperforming RL baselines and improving aesthetics on Stable Diffusion 1.4.