13 citations · 37 across the 17 of their papers we have counts for
5 papers · 1 filter
Lift3D Foundation Policy: Lifting 2D Large-Scale Pretrained Models for Robust 3D Robotic Manipulation
Yueru Jia, Jiaming Liu, Sixiang Chen +8
3D geometric information is essential for manipulation tasks, as robots need to perceive the 3D environment, reason about spatial relationships, and interact with intricate spatial…
Beyond Text-Visual Attention: Exploiting Visual Cues for Effective Token Pruning in VLMs
Qizhe Zhang, Aosong Cheng, Ming Lu +6
Large vision-language models (LVLMs) generally contain significantly more visual tokens than their textual counterparts, resulting in a considerable computational burden. Recent ef…
Training-free Regional Prompting for Diffusion Transformers
Anthony Chen, Jianjin Xu, Wenzhao Zheng +5
Diffusion models have demonstrated excellent capabilities in text-to-image generation. Their semantic understanding (i.e., prompt following) ability has also been greatly improved…
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…