4 citations · 10 across the 32 of their papers we have counts for
10 papers · 1 filter
UniMPA: A Unified Memory-Prediction-Action Model via Action-Grounded Transition Modeling
Wei Li, Rui Shao, Jie He +3
Recent advances in Vision-Language-Action (VLA) models have improved robotic manipulation, yet observation-to-action learning remains limited by a fundamental transition realizabil…
Learning New Tasks via Reusable Skills: Skill-Compositional Experts for Embodied Continual Learning
Shuaike Zhang, Shaokun Wang, Haoyu Tang +2
Embodied Continual Learning (ECL) aims to enable robots to continually acquire new manipulation tasks while retaining previously learned behaviors under closed-loop control. Compar…
ConsisVLA-4D: Advancing Spatiotemporal Consistency in Efficient 3D-Perception and 4D-Reasoning for Robotic Manipulation
Wei Li, Jizhihui Liu, Li Yixing +3
Current Vision-Language-Action (VLA) models primarily focus on mapping 2D observations to actions, but exhibit notable limitations in spatiotemporal perception and reasoning: 1) sp…
Global Prior Meets Local Consistency: Dual-Memory Augmented Vision-Language-Action Model for Efficient Robotic Manipulation
Zaijing Li, Bing Hu, Rui Shao +5
Hierarchical Vision-Language-Action (VLA) models have rapidly become a dominant paradigm for robotic manipulation. It typically comprising a Vision-Language backbone for perception…
DAgger Diffusion Navigation: DAgger Boosted Diffusion Policy for Vision-Language Navigation
Haoxiang Shi, Xiang Deng, Zaijing Li +3
Vision-Language Navigation in Continuous Environments (VLN-CE) requires agents to follow natural language instructions through free-form 3D spaces. Existing VLN-CE approaches typic…
Large VLM-based Vision-Language-Action Models for Robotic Manipulation: A Survey
Rui Shao, Wei Li, Lingsen Zhang +4
Robotic manipulation, a key frontier in robotics and embodied AI, requires precise motor control and multimodal understanding, yet traditional rule-based methods fail to scale or g…