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Open-AoE: An Open Egocentric Manipulation Dataset and Toolchain for Embodied Learning
Zishuo Li, Bowen Yang, Changtao Miao +29
Egocentric videos of human manipulation provide scalable supervision for embodied intelligence, yet existing resources rarely combine low-cost continuous capture, manipulation-leve…
Towards Spatial Supersensing in the Wild
Tianjun Gu, Tianyu Xin, Kuan Zhang +12
Humans can efficiently parse continuous sensory streams, from hours to years, scaffolding an internal world model that grounds spatial reasoning and prediction. To mimic this capac…
ResCue: Residual Spatial Cueing for Language-Conditioned Imitation Learning
Yanzhe Tang, Xinyu Shao, Yuxuan Hu +8
Visual imitation policies must learn which image regions matter for action, whether applying the same operation to different objects or selecting a language-specified target. We in…
GuidedVLA: Specifying Task-Relevant Factors via Plug-and-Play Action Attention Specialization
Xiaosong Jia, Bowen Yang, Zuhao Ge +17
Vision-Language-Action (VLA) models aim for general robot learning by aligning action as a modality within powerful Vision-Language Models (VLMs). Existing VLAs rely on end-to-end…
RePO-VLA: Recovery-Driven Policy Optimization for Vision-Language-Action Models
Weijia Liufu, Xiaoyu Guo, Ruiyi Chen +16
Vision-Language-Action (VLA) models remain brittle in long-horizon, contact-rich manipulation because success-only imitation provides little supervision for execution drift, while…
AoE: Always-on Egocentric Human Video Collection for Embodied AI
Bowen Yang, Zishuo Li, Yang Sun +15
Embodied foundation models require large-scale, high-quality real-world interaction data for pre-training and scaling. However, existing data collection methods suffer from high in…