23 citations · 23 across the 13 of their papers we have counts for
9 papers · 1 filter
EqC: Equilibrium Energy Control for Introspective Lifelong Robot Learning
Haodong Yang, Runhan Huang, Bowen Zhang +7
Long-term robot autonomy depends on more than effective action generation: a policy must recognize when its behavior is no longer sufficiently supported and use assistance to impro…
DexNinja: Learning Robust Dexterous Cutting Policy with a Real-to-Sim-to-Real Data Engine
Haozhe Lou, Runyi Yang, Wanqi Zhong +10
Cutting a piece of food looks effortless in human hands. For a robot, however, every cut is a high-contact interaction with a deformable, elasto-plastic object whose behavior chang…
G0.5: One Autoregressive Stream for Robot Reasoning and Action
Yicheng Liu, Zibin Dong, Baijun Ye +24
The prevailing recipe for Vision-Language-Action (VLA) models couples a pretrained VLM with a separately trained flow-matching action expert. This makes the VLM a context encoder r…
Coarse-to-Control: Action-Token Planning for Vision-Language-Action Models
Jinhao Wu, Shiduo Zhang, Yicheng Liu +9
Most vision-language-action (VLA) models map observations directly to actions without explicit intermediate planning, which limits performance on long-horizon tasks where early mis…
AwareVLN: Reasoning with Self-awareness for Vision-Language Navigation
Wenxuan Guo, Xiuwei Xu, Yichen Liu +7
Vision-and-Language Navigation (VLN) requires an agent to ground language instructions to its own movement within a visual environment. While state-of-the-art methods leverage the…
GesVLA: Gesture-Aware Vision-Language-Action Model Embedded Representations
Wenxuan Guo, Ziyuan Li, Meng Zhang +7
Vision-Language-Action (VLA) models have shown strong potential for general-purpose robot manipulation by unifying perception and action. However, existing VLA systems primarily re…
Generative Control as Optimization: Time Unconditional Flow Matching for Adaptive and Robust Robotic Control
Zunzhe Zhang, Runhan Huang, Yicheng Liu +3
Diffusion models and flow matching have become a cornerstone of robotic imitation learning, yet they suffer from a structural inefficiency where inference is often bound to a fixed…
Fast-WAM: Do World Action Models Need Test-time Future Imagination?
Tianyuan Yuan, Zibin Dong, Yicheng Liu +1
World Action Models (WAMs) have emerged as a promising alternative to Vision-Language-Action (VLA) models for embodied control because they explicitly model how visual observations…
ActionCodec: What Makes for Good Action Tokenizers
Zibin Dong, Yicheng Liu, Shiduo Zhang +8
Vision-Language-Action (VLA) models leveraging the native autoregressive paradigm of Vision-Language Models (VLMs) have demonstrated superior instruction-following and training eff…