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BAS-VLA: A Task-Semantic Action Calibration Framework for VLA Models

The paper proposes BAS-VLA, a task-semantic action calibration framework built on top of a frozen base VLA, designed to address two types of failure: policies producing unnecessary action drift when task semantics are unchanged but appearance varies, and policies continuing along the original trajectory when key semantics such as the target object or constraints are altered.

Part of the event: Proposes BAS-VLA, a task-semantic action calibration framework for VLA

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