5 papers
LM-X: Explainable Vision--Language--Action Modeling via Progress, Event, and Uncertainty Prediction
Jin Lou, Zhiyuan Jing, Xupeng Wang +21
Large-scale vision--language--action (VLA) policies have advanced generalist robot control, yet most remain stimulus-to-action black boxes: actions are exposed, but their explanato…
ACE-Ego-Hand: Repurposing Video Diffusion Models for Occlusion-Robust Egocentric 3D Hand Motion Recovery
Yufei Liu, Xixi Wang, Hao Li +8
Egocentric video offers scalable manipulation data for embodied AI, yet recovering metric 3D hand trajectories remains challenging due to severe object occlusion and frequent out-o…
The Surprising Effectiveness of Video Diffusion Models for Hand Motion Reconstruction
Yuxi Wang, Chengkai Jin, Yufei Liu +6
4D hand motion reconstruction from egocentric video is bottlenecked by clear limitations of existing methods: image-based pipelines depend on a detector that fails under heavy occl…
TRIDENT: Breaking the Hybrid-Safety-Physics Coupling for Provably Safe Multi-Agent Reinforcement Learning
Zijie Meng, Ziwei Li, Yufei Liu +5
Safe coordination in networked cyber-physical systems forces learning algorithms to simultaneously handle hybrid discrete-continuous actions, hard training-time safety constraints,…
ACE-Ego-0: Unifying Egocentric Human and Robotic Data for VLA Pretraining
Hao Li, Ganlong Zhao, Yufei Liu +8
Vision-Language-Action (VLA) models benefit from large-scale and diverse embodied data, yet scaling robot trajectory collection is costly and labor-intensive. Recent advances show…