12 citations · 37 across the 42 of their papers we have counts for
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GigaWorld-1: A Roadmap to Build World Models for Robot Policy Evaluation
GigaWorld Team, Angyuan Ma, Boyuan Wang +24
Evaluating embodied robot foundation models remains a critical bottleneck; unlike large language models efficiently assessed via digital benchmarks, robotic policies require slow,…
iMaC: Translating Actions into Motion and Contact Images for Embodied World Models
Zhenyu Wu, Xiuwei Xu, Yukun Zhou +8
Embodied world models have emerged as a pivotal paradigm for visual robotic decision-making and interactive environment simulation. However, conventional embodied frameworks rely o…
StableIDM: Stabilizing Inverse Dynamics Model against Manipulator Truncation via Spatio-Temporal Refinement
Kerui Li, Zhe Jing, Xiaofeng Wang +6
Inverse Dynamics Models (IDMs) map visual observations to low-level action commands, serving as central components for data labeling and policy execution in embodied AI. However, t…
VAG: Dual-Stream Video-Action Generation for Embodied Data Synthesis
Xiaolei Lang, Yang Wang, Yukun Zhou +10
Recent advances in robot foundation models trained on large-scale human teleoperation data have enabled robots to perform increasingly complex real-world tasks. However, scaling th…
GigaBrain-0: A World Model-Powered Vision-Language-Action Model
GigaBrain Team, Angen Ye, Boyuan Wang +24
Training Vision-Language-Action (VLA) models for generalist robots typically requires large-scale real-world robot data, which is expensive and time-consuming to collect. The ineff…