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cs.RO2026
Hybrid Feedback Sampling for Sample-Efficient Model Predictive Control
Chaoyi Pan, Zeji Yi, John Zhang +3
Thanks to its parallelizability and flexibility, sampling-based Model Predictive Control (MPC) has become widely popular for controlling real-world robotic systems. However, for hi…
cs.LG2026
OGPO: Sample Efficient Full-Finetuning of Generative Control Policies
Sarvesh Patil, Mitsuhiko Nakamoto, Manan Agarwal +14
Generative control policies (GCPs), such as diffusion- and flow-based control policies, have emerged as effective parameterizations for robot learning. This work introduces Off-pol…
cs.LG2026
Global Convergence of Sampling-Based Nonconvex Optimization through Diffusion-Style Smoothing
Zeji Yi, Chaoyi Pan, Guanya Shi +1
Sampling-based optimization (SBO), like cross-entropy method and evolutionary algorithms, has achieved many successes in solving non-convex problems without gradients, yet its conv…