Hy-Embodied-0.5-VLA: From Vision-Language-Action Models to a Real-World Robot Learning Stack
Authors: name: He Zhang, name: Lingzhu Xiang, name: Haitao Lin, name: Zeyu Huang, name: Minghui Wang, name: Dingyan Zhong, name: Yubo Dong, name: Yihao Wu, name: Yongming Rao, name: Dongsheng Zhang, name: Wanjia He, name: Ling Chen, name: Kai Huang, name: Jiahao Chen, name: Sichang Su, name: Xumin Yu, name: Ziyi Wang, name: Chengwei Zhu, name: Xiao Teng, name: Yuchun Guo, name: Yufeng Zhang, name: Yuandong Liu, name: Rui Wang, name: Zisheng Lu, name: Han Hu, name: Zhengyou Zhang
Organization: Tencent Hunyuan

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.