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20232026
most citedOmniSafe: An Infrastructure for Accelerating Safe Reinforcement Learning Research

12 citations · 14 across the 11 of their papers we have counts for

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7 papers · 1 filter

cs.RO2026

Implicit Virtual Leader: Decentralized Vision-Only Relative Pose Estimation for Multi-Robot Formations

Shiyuan Yang, Zelin Wang, Zhijia Tao +8

Classical leader-follower formation control suffers from single points of failure and error propagation, and relies on absolute localization sensors that are ill-suited for GPS-den…

cs.RO2026

FabriVLA: A Lightweight Vision-Language-Action Model with Conformal Action Chunk Uncertainty

Shiyuan Yang, Borong Zhang, Jizheng Zhang +5

Vision-Language-Action (VLA) models have become a leading paradigm for general purpose robotic manipulation, but their computational cost and limited uncertainty awareness hinder p…

cs.RO2026

EDT: Efficient and Effective Decision Transformer with Experience-Aware Sampling for Robotic Manipulation

Kaiyan Zhao, Borong Zhang, Yiming Wang +4

In reinforcement learning (RL) for robotic manipulation, the Decision Transformer (DT) has emerged as an effective framework for addressing long-horizon tasks. However, DT's perfor…

cs.RO2026

RedVLA: Physical Red Teaming for Vision-Language-Action Models

Yuhao Zhang, Borong Zhang, Jiaming Fan +4

The real-world deployment of Vision-Language-Action (VLA) models remains limited by the risk of unpredictable and irreversible physical harm. However, we currently lack effective m…

cs.RO2026

120 Minutes and a Laptop: Minimalist Image-goal Navigation via Unsupervised Exploration and Offline RL

Xiaoming Liu, Borong Zhang, Qingbiao Li +1

The prevailing paradigm for image-goal visual navigation often assumes access to large-scale datasets, substantial pretraining, and significant computational resources. In this wor…

cs.RO2025

VLA-Arena: An Open-Source Framework for Benchmarking Vision-Language-Action Models

Borong Zhang, Jiahao Li, Jiachen Shen +8

While Vision-Language-Action models (VLAs) are rapidly advancing toward generalist robot policies, quantitatively characterizing their capability boundaries and failure modes remai…