AI Research
Closed-Loop Neural Activation Control in Vision-Language-Action Models
Vision-Language-Action (VLA) models can be steered at test time by intervening on semantically meaningful internal directions, but existing methods use a fixed steering coefficient, effectively operating in open loop. This is poorly suited to embodied control, where task state an...
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ArXiv CS.AI
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ArXiv CS.AI
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This research introduces a closed-loop system for controlling AI models that process vision, language, and actions. By dynamically adjusting intervention strength, this method promises more stable and successful task completion in real-world scenarios compared to static control.
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