AIBullisharXiv – CS AI · Mar 37/104
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Dense-Jump Flow Matching with Non-Uniform Time Scheduling for Robotic Policies: Mitigating Multi-Step Inference Degradation
Researchers developed a new robotic policy framework using dense-jump flow matching with non-uniform time scheduling to address performance degradation in multi-step inference. The approach achieves up to 23.7% performance gains over existing baselines by optimizing integration scheduling during training and inference phases.