3 citations · 3 across the 8 of their papers we have counts for
6 papers · 1 filter
Pre-trained Visual Dynamics Representations for Efficient Policy Learning
Hao Luo, Bohan Zhou, Zongqing Lu
Pre-training for Reinforcement Learning (RL) with purely video data is a valuable yet challenging problem. Although in-the-wild videos are readily available and inhere a vast amoun…
Cross-Embodiment Dexterous Grasping with Reinforcement Learning
Haoqi Yuan, Bohan Zhou, Yuhui Fu +1
Dexterous hands exhibit significant potential for complex real-world grasping tasks. While recent studies have primarily focused on learning policies for specific robotic hands, th…
Learning Diverse Bimanual Dexterous Manipulation Skills from Human Demonstrations
Bohan Zhou, Haoqi Yuan, Yuhui Fu +1
Bimanual dexterous manipulation is a critical yet underexplored area in robotics. Its high-dimensional action space and inherent task complexity present significant challenges for…
NOLO: Navigate Only Look Once
Bohan Zhou, Zhongbin Zhang, Jiangxing Wang +1
The in-context learning ability of Transformer models has brought new possibilities to visual navigation. In this paper, we focus on the video navigation setting, where an in-conte…
UniCode: Learning a Unified Codebook for Multimodal Large Language Models
Sipeng Zheng, Bohan Zhou, Yicheng Feng +2
In this paper, we propose \textbf{UniCode}, a novel approach within the domain of multimodal large language models (MLLMs) that learns a unified codebook to efficiently tokenize vi…
Cradle: Empowering Foundation Agents Towards General Computer Control
Weihao Tan, Wentao Zhang, Xinrun Xu +25
Despite the success in specific scenarios, existing foundation agents still struggle to generalize across various virtual scenarios, mainly due to the dramatically different encaps…