AI RESEARCH
HiVLA: A Visual-Grounded-Centric Hierarchical Embodied Manipulation System
arXiv CS.AI
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ArXi:2604.14125v1 Announce Type: cross While end-to-end Vision-Language-Action (VLA) models offer a promising paradigm for robotic manipulation, fine-tuning them on narrow control data often compromises the profound reasoning capabilities inherited from their base Vision-Language Models (VLMs). To resolve this fundamental trade-off, we propose HiVLA, a visual-grounded-centric hierarchical framework that explicitly decouples high-level semantic planning from low-level motor control.