2 citations · 2 across the 12 of their papers we have counts for
6 papers · 1 filter
SEES: A Self-Evolving Embodied System via Failure-Guided VLA Policy Adaptation
Ziwen Li, Hanlue Zhang, Zhenyang Ren +9
Recent vision-language-action (VLA) policies demonstrate promising generalization across diverse short-horizon tasks. However, they remain unreliable on long-horizon tasks, partly…
Suppression Sticks, Locality Is Fragile: A Closed-Loop Target-and-Control Audit of Task-Vector Negation in VLA Policies
Shaoguang Wang, Weiyu Guo, Rushi Dai +3
Task-vector arithmetic offers a closed-form way to modify a model, yet its behavioral locality remains unclear in closed-loop robot control. We present a target-and-control audit o…
How Should Vision-Language-Action Models Use Proprioceptive State?
Yiren Zhao, Ziyang Chen, Ziyang Rao +5
Recent Vision-Language-Action (VLA) models almost universally take robot proprioceptive state as input, yet wire it in incompatible ways -- serialized into text prompts, projected…
Source-Lifted Flow Matching for Intervenable Multimodal Imitation
He Zhang, Ying Sun, Pengteng Li +7
Flow-matching policies are promising for imitation learning because they model complex multimodal action distributions. However, their stochasticity is largely passive: repeated sa…
Spatial Memory for Out-of-Vision Manipulation in Vision-Language-Action
Pengteng Li, Weiyu Guo, He Zhang +4
We introduce SOMA, the Spatial Memory framework for Out-of-Vision Manipulation in Vision-Language-Action (VLA) models. Most existing VLAs implicitly assume that task-relevant objec…
NeuroVLA: A Brain-inspired Embodied Intelligence for Fluid and Fast Reflexive Robotics Control
Weiyu Guo, He Zhang, Pengteng Li +7
Vision-language-action (VLA) models inherit powerful semantic representations from large language models, but carrying over their design priorities can leave the demands of physica…