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Scaling Reinforcement Learning for Diffusion Models via Velocity Matching
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fine-tuningreinforcement learningdiffusion models
2608.23664
Builder Relevance
3h ago80%
Abstract
The paper presents a new method for reward fine-tuning of diffusion models that simplifies the process by using a trajectory-free update based on velocity matching.
Reality Card
Core Claim
The proposed reward-based velocity matching (RVM) method outperforms traditional trajectory-based policy-gradient methods while significantly reducing training costs.
Method / Result
RVM is competitive with or outperforms existing methods under substantially reduced training costs.
Limitations
The paper does not specify limitations or reproducibility concerns.
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