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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 2025Show all

12 papers · 1 filter

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.CV2025

RynnVLA-001: Using Human Demonstrations to Improve Robot Manipulation

Yuming Jiang, Siteng Huang, Shengke Xue +10

This paper presents RynnVLA-001, a vision-language-action(VLA) model built upon large-scale video generative pretraining from human demonstrations. We propose a novel two-stage pre…

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.CV2025

Lumos-1: On Autoregressive Video Generation with Discrete Diffusion from a Unified Model Perspective

Hangjie Yuan, Weihua Chen, Jun Cen +11

Autoregressive large language models (LLMs) have unified a vast range of language tasks, inspiring preliminary efforts in autoregressive (AR) video generation. Existing AR video ge…

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…

cs.CV2025

MathFlow: Enhancing the Perceptual Flow of MLLMs for Visual Mathematical Problems

Shuhang Chen, Hangjie Yuan, Yunqiu Xu +5

Despite strong results on many tasks, multimodal large language models (MLLMs) still underperform on visual mathematical problem solving, especially in reliably perceiving and inte…

cs.CV2025★ 2 cited

LargeAD: Large-Scale Cross-Sensor Data Pretraining for Autonomous Driving

Lingdong Kong, Xiang Xu, Youquan Liu +6

Recent advancements in vision foundation models (VFMs) have revolutionized visual perception in 2D, yet their potential for 3D scene understanding, particularly in autonomous drivi…