16 citations · 19 across the 17 of their papers we have counts for
6 papers · 1 filter
Lift3D-VLA: Lifting VLA Models to 3D Geometry and Dynamics-Aware Manipulation
Jiaming Liu, Qingpo Wuwu, Nuowei Han +8
Recently, Vision-Language-Action (VLA) models have demonstrated strong generalization across diverse tasks. However, effective robotic manipulation in physical environments fundame…
LaST-HD: Learning Latent Physical Reasoning from Scalable Human Data for Robot Manipulation
Jiaming Liu, Yinxi Wang, Chenyang Gu +15
Human-hand demonstrations provide a direct and scalable source of physical interaction data for robot learning. While manual retargeting is indispensable for establishing kinematic…
LaST-R1: Reinforcing Robotic Manipulation via Adaptive Physical Latent Reasoning
Hao Chen, Jiaming Liu, Zhonghao Yan +10
Robotic foundation models require reasoning over complex visual scenes to execute adaptive actions in dynamic environments. While recent studies on latent-reasoning Vision-Language…
Look Before Acting: Enhancing Vision Foundation Representations for Vision-Language-Action Models
Yulin Luo, Hao Chen, Zhuangzhe Wu +10
Vision-Language-Action (VLA) models have recently emerged as a promising paradigm for robotic manipulation, in which reliable action prediction critically depends on accurately int…
TwinRL: Digital Twin-Driven Reinforcement Learning for Real-World Robotic Manipulation
Qinwen Xu, Jiaming Liu, Rui Zhou +11
Despite strong generalization capabilities, Vision-Language-Action (VLA) models remain constrained by the high cost of expert demonstrations and limited real-world interaction. Whi…
LaST: Latent Spatio-Temporal Chain-of-Thought for Robotic Vision-Language-Action Model
Zhuoyang Liu, Jiaming Liu, Hao Chen +11
Vision-Language-Action (VLA) models have recently shown strong generalization, with some approaches seeking to explicitly generate linguistic reasoning traces or predict future obs…