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VGFM: Expressive Robot Policies via Dense Value Guidance in Flow Matching
Recent robot learning paradigms increasingly rely on large offline datasets of robotic interactions to train control policies. Expressive generative models enable rich and multimodal action representations, expanding the capability of this paradigm for complex robotic control. However, policy improv
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