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AdaHVLA: Adaptive Harnesses for Long-Horizon Vision-Language-Action Execution
Vision-language-action (VLA) models offer strong local control and instruction following but often struggle with long-horizon tasks requiring persistent memory and planning. Task harnesses provide persistent context for agent reasoning by retaining task history and tracking progress across execution
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