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20242026
most citedChatVLA: Unified Multimodal Understanding and Robot Control with Vision-Language-Action Model

2 citations · 3 across the 9 of their papers we have counts for

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7 papers · 1 filter

cs.RO2026

Hi-WM: Human-in-the-World-Model for Scalable Robot Post-Training

Yaxuan Li, Zhongyi Zhou, Yefei Chen +5

Post-training is essential for turning pretrained generalist robot policies into reliable task-specific controllers, but existing human-in-the-loop pipelines remain tied to physica…

cs.RO2026

dWorldEval: Scalable Robotic Policy Evaluation via Discrete Diffusion World Model

Yaxuan Li, Zhongyi Zhou, Yefei Chen +2

Evaluating robotics policies across thousands of environments and thousands of tasks is infeasible with existing approaches. This motivates the need for a new methodology for scala…

cs.RO2025

ActiveUMI: Robotic Manipulation with Active Perception from Robot-Free Human Demonstrations

Qiyuan Zeng, Chengmeng Li, Jude St. John +5

We present ActiveUMI, a framework for a data collection system that transfers in-the-wild human demonstrations to robots capable of complex bimanual manipulation. ActiveUMI couples…

cs.RO2025

ChatVLA-2: Vision-Language-Action Model with Open-World Embodied Reasoning from Pretrained Knowledge

Zhongyi Zhou, Yichen Zhu, Junjie Wen +2

Vision-language-action (VLA) models have emerged as the next generation of models in robotics. However, despite leveraging powerful pre-trained Vision-Language Models (VLMs), exist…

cs.RO2025

ObjectVLA: End-to-End Open-World Object Manipulation Without Demonstration

Minjie Zhu, Yichen Zhu, Jinming Li +6

Imitation learning has proven to be highly effective in teaching robots dexterous manipulation skills. However, it typically relies on large amounts of human demonstration data, wh…

cs.RO2025★ 2 cited

ChatVLA: Unified Multimodal Understanding and Robot Control with Vision-Language-Action Model

Zhongyi Zhou, Yichen Zhu, Minjie Zhu +8

Humans possess a unified cognitive ability to perceive, comprehend, and interact with the physical world. Why can't large language models replicate this holistic understanding? Thr…

cs.RO2024★ 1 cited

Diffusion-VLA: Generalizable and Interpretable Robot Foundation Model via Self-Generated Reasoning

Junjie Wen, Minjie Zhu, Yichen Zhu +8

In this paper, we present DiffusionVLA, a novel framework that seamlessly combines the autoregression model with the diffusion model for learning visuomotor policy. Central to our…