13 citations · 26 across the 10 of their papers we have counts for
10 papers
An Intelligent-Cloud Edge Multimodal Interaction System for Robots
Zihan Guo, Xiaoqi Li
Robust human-robot interaction in complex environments requires accurate gesture perception, semantic scene understanding, and reliable task planning under limited onboard computin…
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…
BEVUDA++: Geometric-aware Unsupervised Domain Adaptation for Multi-View 3D Object Detection
Rongyu Zhang, Jiaming Liu, Xiaoqi Li +5
Vision-centric Bird's Eye View (BEV) perception holds considerable promise for autonomous driving. Recent studies have prioritized efficiency or accuracy enhancements, yet the issu…
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…
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…
HybridVLA: Collaborative Diffusion and Autoregression in a Unified Vision-Language-Action Model
Jiaming Liu, Hao Chen, Pengju An +12
A fundamental objective of manipulation policy design is to endow robots to comprehend human instructions, reason about scene cues, and execute generalized actions in dynamic envir…
RoboMamba: Efficient Vision-Language-Action Model for Robotic Reasoning and Manipulation
Jiaming Liu, Mengzhen Liu, Zhenyu Wang +7
A fundamental objective in robot manipulation is to enable models to comprehend visual scenes and execute actions. Although existing Vision-Language-Action (VLA) models for robots…
A Self-Correcting Vision-Language-Action Model for Fast and Slow System Manipulation
Chenxuan Li, Jiaming Liu, Guanqun Wang +8
Recently, some studies have integrated Multimodal Large Language Models into robotic manipulation, constructing vision-language-action models (VLAs) to interpret multimodal informa…
LiDAR-LLM: Exploring the Potential of Large Language Models for 3D LiDAR Understanding
Senqiao Yang, Jiaming Liu, Ray Zhang +7
Recently, Large Language Models (LLMs) and Multimodal Large Language Models (MLLMs) have shown promise in instruction following and 2D image understanding. While these models are p…
Unsupervised Spike Depth Estimation via Cross-modality Cross-domain Knowledge Transfer
Jiaming Liu, Qizhe Zhang, Xiaoqi Li +5
Neuromorphic spike data, an upcoming modality with high temporal resolution, has shown promising potential in autonomous driving by mitigating the challenges posed by high-velocity…