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Xu et al.: compact frozen-VLA interface for online actor–critic adaptation

Contribution grade

Sample-efficient robot reinforcement learning · Human-designed research method or resource

Reference score45,000Provisional editorial estimate of this exact contribution; its grade is assessed separately.

What changed

Exposed a compact task-relevant token from a pretrained VLA and trained lightweight actor/critic heads with a regularizer anchoring actions to the frozen VLA, enabling online adaptation of precise manipulation.

Scientific scope

Exposed a compact task-relevant token from a pretrained VLA and trained lightweight actor/critic heads with a regularizer anchoring actions to the frozen VLA, enabling online adaptation of precise manipulation. Actor–critic, residual control, frozen representations and VLA pretraining are inherited. Acquired delta is the learned compact interface/anchored adaptation recipe, not onlineRL itself. Four task improvements do not imply arbitrary-task sample efficiency or physical safety.

Evidence

The linked original sources describe the stated contribution and its evidence limits. WRS has not independently rerun the experiments or certified a proof. Actor–critic, residual control, frozen representations and VLA pretraining are inherited. Acquired delta is the learned compact interface/anchored adaptation recipe, not onlineRL itself. Four task improvements do not imply arbitrary-task sample efficiency or physical safety.

Contributors

Provisional WRS assessment, edition 2026-10-16.1. Independent expert calibration is pending. This grade does not certify correctness or assign ownership.

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