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20232026
most citedDecision Mamba: A Multi-Grained State Space Model with Self-Evolution Regularization for Offline RL

1 citations · 2 across the 18 of their papers we have counts for

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8 papers · 1 filter

cs.CV2025

Task-Aware 3D Affordance Segmentation via 2D Guidance and Geometric Refinement

Lian He, Meng Liu, Qilang Ye +3

Understanding 3D scene-level affordances from natural language instructions is essential for enabling embodied agents to interact meaningfully in complex environments. However, thi…

cs.RO2025

F1: A Vision-Language-Action Model Bridging Understanding and Generation to Actions

Qi Lv, Weijie Kong, Hao Li +7

Executing language-conditioned tasks in dynamic visual environments remains a central challenge in embodied AI. Existing Vision-Language-Action (VLA) models predominantly adopt rea…

cs.RO2025

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…

cs.RO2025

STAR: Learning Diverse Robot Skill Abstractions through Rotation-Augmented Vector Quantization

Hao Li, Qi Lv, Rui Shao +4

Transforming complex actions into discrete skill abstractions has demonstrated strong potential for robotic manipulation. Existing approaches mainly leverage latent variable models…

cs.RO2025

Few-Shot Vision-Language Action-Incremental Policy Learning

Mingchen Song, Xiang Deng, Guoqiang Zhong +5

Recently, Transformer-based robotic manipulation methods utilize multi-view spatial representations and language instructions to learn robot motion trajectories by leveraging numer…

cs.RO2025

Spatial-Temporal Graph Diffusion Policy with Kinematic Modeling for Bimanual Robotic Manipulation

Qi Lv, Hao Li, Xiang Deng +6

Despite the significant success of imitation learning in robotic manipulation, its application to bimanual tasks remains highly challenging. Existing approaches mainly learn a poli…

cs.CV2025

3D-AffordanceLLM: Harnessing Large Language Models for Open-Vocabulary Affordance Detection in 3D Worlds

Hengshuo Chu, Xiang Deng, Qi Lv +4

3D Affordance detection is a challenging problem with broad applications on various robotic tasks. Existing methods typically formulate the detection paradigm as a label-based sema…

cs.CV2025

Embodied Crowd Counting

Runling Long, Yunlong Wang, Jia Wan +5

Occlusion is one of the fundamental challenges in crowd counting. In the community, various data-driven approaches have been developed to address this issue, yet their effectivenes…