mlsanityData to 7 Oct 2026

Human-AI Co-Embodied Intelligence for Scientific Experimentation and Manufacturing

arXiv 2511.02071 ↗First posted 3 Nov 2025cs.AIcited by 0

On the map: LLM agents and tool use → Multimodal and embodied agents

Abstract (arXiv)

Scientific experimentation and manufacturing rely on prolonged protocol development and complex, multi-step implementation, which require continuous human expertise for precise execution and decision-making, limiting interpretability and scalability. Here, we introduce human-artificial intelligence (AI) co-embodied intelligence, a new form of physical AI that unites human researchers, agentic AI, and wearable hardware. In this paradigm, humans provide precise execution, while agentic AI contributes contextual reasoning, adaptive planning, and analysis. The wearable interface continuously captures experimentation and manufacturing, facilitating seamless communication between humans and AI. We instantiate this paradigm in a microfabrication cleanroom, leading to the agentic-physical experimentation (APEX) system which understands fabrication procedure with accuracy 51% higher than state-of-the-art multimodal large language models/vision language models (LLMs/VLMs), detects and corrects fabrication errors in real-time, and transfers procedural expertise to novice users. Critically, APEX system enables the co-development of fabrication protocols in cleanrooms, overcoming the incompatibility of elastomeric materials in standard microfabrication processes and enabling previously unattainable fabrication outcomes, as demonstrated by the wafer-scale realization of brain-level soft neural probe capable of single-unit-resolution neural recording. These results establish the human-AI co-embodied intelligence that extends agentic reasoning beyond computation into the physical domain, transforming scientific experimentation and manufacturing into autonomous, traceable, interpretable and scalable processes.

Key facts. No citing papers in the map yet (data through 7 Oct 2026). Placed in Multimodal and embodied agents, one of 16 directions in LLM agents and tool use. Builds on 13 of its 48 references that are in the map. First posted on arXiv 3 Nov 2025.

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13 of 48 references.

References · 13

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1 more
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  4. 2025Virtuous Machines: Towards Artificial General Science
  5. 2024MetaScientist: A Human-AI Synergistic Framework for Automated Mechanical Metamaterial Design
  6. 2025Generative Multi-Agent Collaboration in Embodied AI: A Systematic Review
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