16 citations · 19 across the 17 of their papers we have counts for
12 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…
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…
RoboMIND 2.0: A Multimodal, Bimanual Mobile Manipulation Dataset for Generalizable Embodied Intelligence
Chengkai Hou, Kun Wu, Jiaming Liu +30
While data-driven imitation learning has revolutionized robotic manipulation, current approaches remain constrained by the scarcity of large-scale, diverse real-world demonstration…
ManualVLA: A Unified VLA Model for Chain-of-Thought Manual Generation and Robotic Manipulation
Chenyang Gu, Jiaming Liu, Hao Chen +9
Vision-Language-Action (VLA) models have recently emerged, demonstrating strong generalization in robotic scene understanding and manipulation. However, when confronted with long-h…
MLA: A Multisensory Language-Action Model for Multimodal Understanding and Forecasting in Robotic Manipulation
Zhuoyang Liu, Jiaming Liu, Jiadong Xu +10
Vision-language-action models (VLAs) have shown generalization capabilities in robotic manipulation tasks by inheriting from vision-language models (VLMs) and learning action gener…
RwoR: Generating Robot Demonstrations from Human Hand Collection for Policy Learning without Robot
Liang Heng, Xiaoqi Li, Shangqing Mao +9
Recent advancements in imitation learning have shown promising results in robotic manipulation, driven by the availability of high-quality training data. To improve data collection…
AC-DiT: Adaptive Coordination Diffusion Transformer for Mobile Manipulation
Sixiang Chen, Jiaming Liu, Siyuan Qian +9
Recently, mobile manipulation has attracted increasing attention for enabling language-conditioned robotic control in household tasks. However, existing methods still face challeng…
Fast-in-Slow: A Dual-System Foundation Model Unifying Fast Manipulation within Slow Reasoning
Hao Chen, Jiaming Liu, Chenyang Gu +8
Generalized policy and execution efficiency constitute the two critical challenges in robotic manipulation. While recent foundation policies benefit from the common-sense reasoning…
RoboMIND: Benchmark on Multi-embodiment Intelligence Normative Data for Robot Manipulation
Kun Wu, Chengkai Hou, Jiaming Liu +34
In this paper, we introduce RoboMIND (Multi-embodiment Intelligence Normative Data for Robot Manipulation), a dataset containing 107k demonstration trajectories across 479 diverse…