Hy-Embodied-0.5-VLA: From Vision-Language-Action Models to a Real-World Robot Learning Stack
HyVLA-0.5 presents an end-to-end robot learning stack spanning data collection, training, reinforcement learning, and real-world deployment.
Excerpt
He Zhang, Lingzhu Xiang, Haitao Lin, Zeyu Huang, Minghui Wang — 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.
Read at source: https://arxiv.org/abs/2606.14409