7 citations · 20 across the 26 of their papers we have counts for
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cs.CV2024★ 7 cited
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…
cs.CV2024★ 2 cited
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…
cs.CV2024★ 1 cited
No Time to Train: Empowering Non-Parametric Networks for Few-shot 3D Scene Segmentation
Xiangyang Zhu, Renrui Zhang, Bowei He +6
To reduce the reliance on large-scale datasets, recent works in 3D segmentation resort to few-shot learning. Current 3D few-shot segmentation methods first pre-train models on 'see…