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20212026
most citedSegment Any Point Cloud Sequences by Distilling Vision Foundation Models

29 citations · 70 across the 41 of their papers we have counts for

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Showing 2025 · cs.ROShow all

8 papers · 2 filters

cs.RO2025

Token Expand-Merge: Training-Free Token Compression for Vision-Language-Action Models

Yifan Ye, Jiaqi Ma, Jun Cen +1

Vision-Language-Action (VLA) models pretrained on large-scale multimodal datasets have emerged as powerful foundations for robotic perception and control. However, their massive sc…

cs.RO2025

VLSA: Vision-Language-Action Models with Plug-and-Play Safety Constraint Layer

Songqiao Hu, Zeyi Liu, Shuang Liu +5

Vision-Language-Action (VLA) models have demonstrated remarkable capabilities in generalizing across diverse robotic manipulation tasks. However, deploying these models in unstruct…

cs.RO2025

HiMaCon: Discovering Hierarchical Manipulation Concepts from Unlabeled Multi-Modal Data

Ruizhe Liu, Pei Zhou, Qian Luo +4

Effective generalization in robotic manipulation requires representations that capture invariant patterns of interaction across environments and tasks. We present a self-supervised…

cs.RO2025

RynnVLA-002: A Unified Vision-Language-Action and World Model

Jun Cen, Siteng Huang, Yuqian Yuan +11

We introduce RynnVLA-002, a unified Vision-Language-Action (VLA) and world model. The world model leverages action and visual inputs to predict future image states, learning the un…

cs.RO2025

Self-evolved Imitation Learning in Simulated World

Yifan Ye, Jun Cen, Jing Chen +1

Imitation learning has been a trend recently, yet training a generalist agent across multiple tasks still requires large-scale expert demonstrations, which are costly and labor-int…

cs.RO2025

Towards Affordance-Aware Robotic Dexterous Grasping with Human-like Priors

Haoyu Zhao, Linghao Zhuang, Xingyue Zhao +10

A dexterous hand capable of generalizable grasping objects is fundamental for the development of general-purpose embodied AI. However, previous methods focus narrowly on low-level…

cs.RO2025

WorldVLA: Towards Autoregressive Action World Model

Jun Cen, Chaohui Yu, Hangjie Yuan +9

We present WorldVLA, an autoregressive action world model that unifies action and image understanding and generation. Our WorldVLA intergrates Vision-Language-Action (VLA) model an…

cs.RO2025

Generative Artificial Intelligence in Robotic Manipulation: A Survey

Kun Zhang, Peng Yun, Jun Cen +11

This survey provides a comprehensive review on recent advancements of generative learning models in robotic manipulation, addressing key challenges in the field. Robotic manipulati…