arXiv:2605. 22183v3 Announce Type: replace-cross Abstract: Vision-Language-Action (VLA) models have emerged as a promising paradigm for generalist robotic manipulation.
By Weilong Guo, Yuchen Wang, Renping Zhou, Yunfeng Zhang, Rui Fang, Yuyang Pang, Wenda Xu, Gao Huang
arXiv:2603. 06001v2 Announce Type: replace-cross Abstract: Vision-Language-Action (VLA) models enable robots to perform manipulation tasks directly from natural language instructions and are increasingly viewed as a foundation for generalist robotic policies.
By Ninghao Zhang, Bin Zhu, Shijie Zhou, Jingjing Chen
arXiv:2511. 18960v4 Announce Type: replace Abstract: Vision-Language-Action (VLA) models have shown remarkable progress in embodied tasks recently, but most methods process visual observations independently at each timestep.
By Lei Xiao, Jifeng Li, Juntao Gao, Feiyang Ye, Yan Jin, Jingjing Qian, Jing Zhang, Yong Wu, Xiaoyuan Yu
arXiv:2606. 12299v1 Announce Type: cross Abstract: Vision-Language-Action (VLA) models provide a natural language interface to robot control, but the mapping from language to behavior is often brittle and unintuitive: semantically similar instructions can induce drastically different behaviors, while some capabilities may not be elicitable through prompting alone.
By Hyun Joe Jeong, Gokul Swamy, Andrea Bajcsy
arXiv:2606. 10918v1 Announce Type: cross Abstract: The recent trend in scaling models for robot learning has resulted in impressive policies that can perform various manipulation tasks and generalize to novel scenarios.
By Artur Kuramshin, \"Ozg\"ur Aslan, Cyrus Neary, Glen Berseth
arXiv:2606. 09572v1 Announce Type: cross Abstract: Vision-language-action models have shown strong promise for robot manipulation, yet raw language is primarily needed to specify task intent rather than to be repeatedly processed during high-frequency low-level execution.
By Jiacheng Li, Yize Guo, Jiabin Guo, Qingchen Liu, Jiahu Qin