3 citations · 4 across the 9 of their papers we have counts for
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cs.RO2025
Scaling Cross-Embodiment World Models for Dexterous Manipulation
Zihao He, Bo Ai, Tongzhou Mu +6
Cross-embodiment learning seeks to build generalist robots that learn from and operate across diverse morphologies, but differences in kinematics and action spaces hinder data shar…
cs.CV2025★ 1 cited
UI-Venus Technical Report: Building High-performance UI Agents with RFT
Zhangxuan Gu, Zhengwen Zeng, Zhenyu Xu +21
We present UI-Venus, a native UI agent that takes only screenshots as input based on a multimodal large language model. UI-Venus achieves SOTA performance on both UI grounding and…
cs.RO2025
Learning Adaptive Dexterous Grasping from Single Demonstrations
Liangzhi Shi, Yulin Liu, Lingqi Zeng +3
How can robots learn dexterous grasping skills efficiently and apply them adaptively based on user instructions? This work tackles two key challenges: efficient skill acquisition f…