titleHy-Embodied-0.5-VLA: From Vision-Language-Action Models to a Real-World Robot Learning Stack
authorsHe Zhang, Lingzhu Xiang, Haitao Lin, Zeyu Huang, Minghui Wang, Dingyan Zhong, Yubo Dong, Yihao Wu, Yongming Rao, Dongsheng Zhang, Wanjia He, Ling Chen, Kai Huang, Jiahao Chen, Sichang Su, Xumin Yu, Ziyi Wang, Chengwei Zhu, Xiao Teng, Yuchun Guo, Yufeng Zhang, Yuandong Liu, Rui Wang, Zisheng Lu, Han Hu, Zhengyou Zhang
date2026-06-12
venuearXiv (preprint, not peer reviewed)
idarXiv:2606.14409
affiliationTencent Hunyuan
upvotes15 (Hugging Face Daily Papers, 2026-11-01)
linksabs pdf hf
primerVision-language-action models
abstractIn 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.

cite

@misc{zhang2026hy,
  title={Hy-Embodied-0.5-VLA: From Vision-Language-Action Models to a Real-World Robot Learning Stack},
  author={He Zhang and Lingzhu Xiang and Haitao Lin and Zeyu Huang and Minghui Wang and Dingyan Zhong and Yubo Dong and Yihao Wu and Yongming Rao and Dongsheng Zhang and Wanjia He and Ling Chen and Kai Huang and Jiahao Chen and Sichang Su and Xumin Yu and Ziyi Wang and Chengwei Zhu and Xiao Teng and Yuchun Guo and Yufeng Zhang and Yuandong Liu and Rui Wang and Zisheng Lu and Han Hu and Zhengyou Zhang},
  year={2026},
  eprint={2606.14409},
  archivePrefix={arXiv},
  url={https://arxiv.org/abs/2606.14409}
}