3 papers
cs.RO2026
LabEvolver: Training-Free Experience Evolution for Safe and Grounded Wet-Lab Agents
Jingya Wang, Yuyang Gao, Liuzhenghao Lv +2
We introduce LabEvolver, a training-free framework that equips safe and grounded wet-lab agents with episodic memory from execution experience. LabEvolver couples a state-grounded…
cs.AI2026
Beyond World-Frame Action Heads: Motion-Centric Action Frames for Vision-Language-Action Models
Huoren Yang, Jianchao Zhao, Hu Yusong +7
Vision-Language-Action (VLA) models have advanced rapidly with stronger backbones, broader pre-training, and larger demonstration datasets, yet their action heads remain largely ho…
cs.RO2026
Retrieve-then-Steer: Online Success Memory for Test-Time Adaptation of Generative VLAs
Jianchao Zhao, Huoren Yang, Yusong Hu +6
Vision-Language-Action (VLA) models show strong potential for general-purpose robotic manipulation, yet their closed-loop reliability often degrades under local deployment conditio…