3 papers
cs.RO2026
FolDeX: A Physical-World Benchmark for Long-Horizon Robotic Manipulation of Deformable Objects
Chenhuan Liu, Yi Xu, Feng Wu +7
Embodied AI, including vision-language-action and world-action models, must operate reliably in the physical world. Yet methods that perform well in simulation can degrade substant…
cs.RO2026
DSWAM: A Dual-System World Action Foundation Model for Fine-Grained Robot Manipulation
Jian Zhu, Jianjun Zhang, Taiyi Su +10
World Action Models (WAMs) provide a promising alternative to Vision-Language-Action (VLA) policies by using video-based world modeling as dense supervision for robot action learni…
cs.RO2026
DeMaVLA: A Vision-Language-Action Foundation Model for Generalizable Deformable Manipulation
Taiyi Su, Jian Zhu, Tianjian Wang +9
Real-world household robots require Vision-Language-Action (VLA) foundation models that can acquire reusable manipulation skills across diverse objects, task conditions, and househ…