7 papers · 1 filter
VLA-Fabric: Learning Interaction for Composable Multi-Arm VLA Agents
Chenglong Zhang, Shuaijun Liu, Feiyang You +3
Vision-language-action (VLA) models are rapidly expanding what individual robots can accomplish, yet many real-world manipulation settings require multiple arms to operate as a coo…
MimicX: Policy-in-the-Loop Supervision Refinement for Video-Driven Humanoid Motion Tracking
Shuaijun Liu, Chenglong Zhang, Xuhao Liu +7
Human videos provide rich motion targets for humanoid learning, yet visually plausible references can still produce persistent failures under physics-based execution. These failure…
D-JEPA: A Decision-Aligned Latent World Model
Shuaijun Liu, Chengyu Wu, Qifu Wen +5
Latent world models predict the consequences of actions, but accurate prediction does not guarantee that latent distance reflects which candidate will execute successfully. We iden…
Beyond Appearance Shifts: Task-Semantic Action Calibration for VLA Models
Shuaijun Liu, Feiyang You, Chengyu Wu +6
Vision-language-action (VLA) models have achieved strong performance in embodied manipulation, but still struggle to distinguish between changes that should preserve behavior and t…
CoWAM: Coordination Contracts for Selective Policy Intervention with WAMs
Shuaijun Liu, Qifu Wen, Shuyang Hao +5
World Action Models (WAMs) augment robot policies with action-conditioned predicted futures, but a plausible future alone does not justify changing the action that a bimanual polic…
When Replanning Becomes the Bottleneck: Budgeted Replanning for Embodied Agents
Shuaijun Liu, Feiyang You, Xingwei Chen +1
Embodied agents replan frequently to recover from execution drift, partial observability, and coordination hazards, but each LLM-based replanning call can consume an accumulated te…
The Gate, Not the Cache: Gate Provenance Bounds the Closed-Loop Reliability of Training-Free VLA Token Skipping
Qi Luo, Shuaijun Liu, Hao Zhao +5
Token skipping is a widely used training-free way to accelerate vision--language--action (VLA) models by bypassing computation for most visual tokens at each control step according…