most citedLLM-based Robot Task Planning with Exceptional Handling for General Purpose Service Robots

3 citations · 7 across the 8 of their papers we have counts for

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cs.RO2025

HiF-VLA: Hindsight, Insight and Foresight through Motion Representation for Vision-Language-Action Models

Minghui Lin, Pengxiang Ding, Shu Wang +7

Vision-Language-Action (VLA) models have recently enabled robotic manipulation by grounding visual and linguistic cues into actions. However, most VLAs assume the Markov property,…

cs.RO2025

VLA-Adapter: An Effective Paradigm for Tiny-Scale Vision-Language-Action Model

Yihao Wang, Pengxiang Ding, Lingxiao Li +13

Vision-Language-Action (VLA) models typically bridge the gap between perceptual and action spaces by pre-training a large-scale Vision-Language Model (VLM) on robotic data. While t…

cs.RO2025★ 1 cited

Long-VLA: Unleashing Long-Horizon Capability of Vision Language Action Model for Robot Manipulation

Yiguo Fan, Pengxiang Ding, Shuanghao Bai +10

Vision-Language-Action (VLA) models have become a cornerstone in robotic policy learning, leveraging large-scale multimodal data for robust and scalable control. However, existing…

cs.RO2025★ 2 cited

OpenHelix: A Short Survey, Empirical Analysis, and Open-Source Dual-System VLA Model for Robotic Manipulation

Can Cui, Pengxiang Ding, Wenxuan Song +10

Dual-system VLA (Vision-Language-Action) architectures have become a hot topic in embodied intelligence research, but there is a lack of sufficient open-source work for further per…

cs.RO2025

MoRE: Unlocking Scalability in Reinforcement Learning for Quadruped Vision-Language-Action Models

Han Zhao, Wenxuan Song, Donglin Wang +4

Developing versatile quadruped robots that can smoothly perform various actions and tasks in real-world environments remains a significant challenge. This paper introduces a novel…

cs.RO2025★ 1 cited

Humanoid-VLA: Towards Universal Humanoid Control with Visual Integration

Pengxiang Ding, Jianfei Ma, Xinyang Tong +13

This paper addresses the limitations of current humanoid robot control frameworks, which primarily rely on reactive mechanisms and lack autonomous interaction capabilities due to d…

cs.RO2024

QUART-Online: Latency-Free Large Multimodal Language Model for Quadruped Robot Learning

Xinyang Tong, Pengxiang Ding, Yiguo Fan +9

This paper addresses the inherent inference latency challenges associated with deploying multimodal large language models (MLLM) in quadruped vision-language-action (QUAR-VLA) task…

cs.RO2024★ 3 cited

LLM-based Robot Task Planning with Exceptional Handling for General Purpose Service Robots

Ruoyu Wang, Zhipeng Yang, Zinan Zhao +3

The development of a general purpose service robot for daily life necessitates the robot's ability to deploy a myriad of fundamental behaviors judiciously. Recent advancements in t…