4 papers
Frame-Level Temporal Alignment for Human-to-Robot Visual Adaptation
Xizhe Zhang, Jingfeng Zhang, Zirun Zhou +1
Transferring visual representations pretrained on human videos to robot manipulation requires learning reliable correspondences between human and robot demonstrations. However, pai…
Model-agnostic Adversarial Attack and Defense for Vision-Language-Action Models
Haochuan Xu, Yun Sing Koh, Shuhuai Huang +4
Vision-Language-Action (VLA) models have achieved revolutionary progress in robot learning, enabling robots to execute complex physical robot tasks from natural language instructio…
Goal-oriented Backdoor Attack against Vision-Language-Action Models via Physical Objects
Zirun Zhou, Zhengyang Xiao, Haochuan Xu +3
Recent advances in vision-language-action (VLA) models have greatly improved embodied AI, enabling robots to follow natural language instructions and perform diverse tasks. However…
A tutorial note on collecting simulated data for vision-language-action models
Heran Wu, Zirun Zhou, Jingfeng Zhang
Traditional robotic systems typically decompose intelligence into independent modules for computer vision, natural language processing, and motion control. Vision-Language-Action (…