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Generative planners based on diffusion/flow matching can learn to synthesize long-horizon trajectories from demonstrations. However, real-world deployment requires (i) enforcing safety constraints during execution and (ii) tight online replanning at fast execution rates. Prior safe diffusion/flow planners generate the...
A theoretical, signature-based formulation of the LRH for VLA that unifies representations and policies is developed, and a signature generalized linear model for stochastic action chunks is introduced for stochastic action chunks.
Symmetric VLA Distillation (SymVD), a distillation framework that transfers knowledge from a large VLA teacher to a compact student policy by explicitly exploiting geometric symmetries in manipulation tasks, consistently improves over standard distillation and also outperforms SAC in terms of sample efficiency and gene...
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