1 citations · 1 across the 22 of their papers we have counts for
18 papers · 1 filter
KineBench: Benchmarking Embodied World Models via IDM-Free Kinematic Grounding
Zeyu Liu, Zhangzhe Zhu, Yang Zhang +3
Evaluating the physical consistency of embodied world models(EWMs) is a critical open challenge. While closed-loop evaluation via simulator rollouts offers a more faithful assessme…
EDAR: Learning Environment-Dependent Action Representations for Robotic Manipulation
Yuecheng Xu, Tong Yang, Jingkai Jia +3
Learning effective action representations is critical for robotic manipulation, where raw control trajectories are often noisy, redundant, and difficult to model directly. Existing…
SpaceVLN: A Zero-Shot Vision-and-Language Navigation Agent with Online Spatial Cognitive Memory and Reasoning
Yucheng Deng, Pingrui Lai, Xinhai Li +5
Vision-and-Language Navigation in continuous environments requires agents to understand the spatial structure of previously unseen environments in order to follow language instruct…
OASIS: From Simulation Data Collection to Real-World Humanoid Loco-Manipulation
Zehao Yu, Jiakun Zheng, Weiji Xie +4
Recent progress in robot manipulation has been largely driven by learning from large-scale demonstrations. For humanoid robot loco-manipulation tasks, however, existing data source…
VISTA: Vision-Grounded and Physics-Validated Adaptation of UMI data for VLA Training
Siyuan Yang, Linzheng Guo, Ouyang Lu +10
Universal Manipulation Interface (UMI) enables scalable real-world robot data collection without hardware-specific teleoperation, yet leveraging UMI data to train large-scale Visio…
GN0: Toward a Unified Paradigm for Generation, Evaluation, and Policy Learning in Visual-Language Navigation
Xinhai Li, Xiaotao Zhang, Yuehao Huang +10
Embodied navigation connects intelligent agents with the physical world and is fundamental for general robotic intelligence. Limited availability and quality of navigation data hav…