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GeoAAC is proposed, a geometry-based adaptive action chunking method for flow-based VLA policies that adjusts the action horizon according to the reliability of the current action prediction, with geometric variation across action prefixes remaining positively correlated with predictive uncertainty.
Query-grounded visual sampling can boost long video understanding in LVLMs by over 11% without the need for extensive training.
