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arxiv:2606.14409
Hy-Embodied-0.5-VLA: From Vision-Language-Action Models to a Real-World Robot Learning Stack
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Abstract
HyVLA-0.5 is an end-to-end robotic learning system that integrates data collection, model design, pre-training, fine-tuning, and reinforcement learning for real-world deployment.
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In this report, we present Hy-Embodied-0.5-VLA, abbreviated as HyVLA-0.5, an end-to-end system that spans the full robot learning stack: data collection, model design, continued pre-training and supervised fine-tuning, RL post-training, and real-world deployment. Each component serves a distinct role in this stack.
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