Retrieve to Act: Motion Primitive Graph Retrieval for Robust VLA Execution
Overview
Source roundup from published reports. Claims below are attributed to their publishers, not independently verified. arXiv Robotics — research abstracts: Retrieve to Act: Motion Primitive Graph Retrieval for Robust VLA Execution. This research proposes R2A, a framework that enhances the robustness of Vision-Language-Action (VLA) policies by treating out-of-distribution visual shifts as a geometric motion primitive retrieval problem. R2A uses a gr…
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- 2026-10-30T17:34:49.358Z · evidence updated · source revision 1. Evidence extraction was updated; current source attributions are shown above.
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- arXiv Robotics — research abstractsSignalRetrieve to Act: Motion Primitive Graph Retrieval for Robust VLA Execution
This research proposes R2A, a framework that enhances the robustness of Vision-Language-Action (VLA) policies by treating out-of-distribution visual shifts as a geometric motion primitive retrieval problem. R2A uses a graph neural network to dynamically localize robot execution and harmonize retrieved geometric priors with predicted actions, achieving significant improvements in simulation and real-world benchmarks without policy finetuning.
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