dFlowGRPO is a new rate-aware RL method for discrete flow models that outperforms prior GRPO approaches on image generation and matches continuous flow models while supporting broad probability paths.
arXiv preprint arXiv:2504.01031 , year=
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A nonparametric model-agnostic framework purifies noisy labels with a small clean dataset for robust classification under label noise.
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dFlowGRPO: Rate-Aware Policy Optimization for Discrete Flow Models
dFlowGRPO is a new rate-aware RL method for discrete flow models that outperforms prior GRPO approaches on image generation and matches continuous flow models while supporting broad probability paths.
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Model-agnostic information transfer and fusion for classification with label noise
A nonparametric model-agnostic framework purifies noisy labels with a small clean dataset for robust classification under label noise.