activity
20232026
most citedHuman-in-the-loop Online Rejection Sampling for Robotic Manipulation

1 citations · 1 across the 9 of their papers we have counts for

collaborators
Showing cs.ROShow all

13 papers · 1 filter

cs.RO2026

Native Video-Action Pretraining for Generalizable Robot Control

Qihang Zhang, Lin Li, Luyao Zhang +26

The advent of video-action models offers a promising path for robot control. Nevertheless, we argue that repurposing video generative models designed for digital content creation i…

cs.RO2026

A Closed-Loop Multi-Agent Framework for Robust Multi-Robot Manipulation

Yi-Xiang He, Lan Wei, Haoming Cen +6

Multi-robot systems provide the parallelism and redundancy necessary for long-horizon tasks, while Large Language Models (LLMs) offer the reasoning capabilities to decompose these…

cs.RO2026

BrickCraft: Visuomotor Skill Composition with Situated Manual Guidance for Long-Horizon Interlocking Brick Assembly

Jichuan Yu, Bowei Li, Zhenran Tang +4

Autonomous robotic assembly of interlocking bricks demands seamless integration of long-horizon task reasoning, spatial grounding, and fine-grained manipulation. This paper present…

cs.RO20251 cited

Human-in-the-loop Online Rejection Sampling for Robotic Manipulation

Guanxing Lu, Rui Zhao, Haitao Lin +2

Reinforcement learning (RL) is widely used to produce robust robotic manipulation policies, but fine-tuning vision-language-action (VLA) models with RL can be unstable due to inacc…

cs.RO2025

RESample: A Robust Data Augmentation Framework via Exploratory Sampling for Robotic Manipulation

Yuquan Xue, Guanxing Lu, Zhenyu Wu +4

Vision-Language-Action (VLA) models have shown strong manipulation capability when trained with large-scale imitation learning datasets. However, these datasets that predominantly…

cs.RO2025

RoDyn: Taming Interactive Robot-Dynamic 2.5D World Model for Robotic Manipulation

Chuanrui Zhang, Zhengxian Wu, Guanxing Lu +2

Learned world models hold significant potential as neural simulators for robotic manipulation. However, prevalent 2D video-based models inherently lack the spatial and kinematic re…