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Matching papers

HumanCLAW: Can Vision-Language Models Act Through a Body?

65 upvotes · 29 JUL 2026 · Siyao Li, Jiawei Gu, Shuai Liu et al.

This paper evaluates whether vision-language models can act through a physical body and how they can make decisions about what actions to take, without being hindered by issues like balance and motor control. Practitioners in AI and robotics might care because understanding how models interact with their physical bodies can help improve their ability to navigate and interact with the world.

vision-language modelsembodied intelligenceaction intelligencemotor controlphysical interaction

Open-AoE: An Open Egocentric Manipulation Dataset and Toolchain for Embodied Learning

61 upvotes · 15 JUL 2026 · Zishuo Li, Bowen Yang, Changtao Miao et al.

This paper introduces Open-AoE, an open dataset and toolchain for egocentric manipulation learning, providing a scalable and structured platform for training embodied models. Practitioners can use Open-AoE to improve their robot learning models, especially those focused on human-robot interaction and embodied intelligence.

egocentric videosmanipulation tasksembodied intelligencerobot learningdata annotation

ACE-Data-0: Human-Centric Ambient Capture as Embodied Data Engine

36 upvotes · 30 JUL 2026 · Yukang Cao, Haozhe Xie, Beichen Wen et al.

This paper introduces a new dataset called ACE-Data-0, which provides a comprehensive and synchronized record of human behavior in real-world environments, capturing various aspects of embodied intelligence such as perception, action, and interaction. Practitioners in the field of embodied AI and machine learning can use this dataset to develop more sophisticated models that can learn from human demonstrations and perform tasks that involve complex manipulation, locomotion, and interaction.

embodied intelligencemultimodal datahuman-robot interactionperception-action loopimitation learningworld models