# LabOS: The AI-XR Co-Scientist That Sees and Works With Humans

arXiv: https://arxiv.org/abs/2510.14861 · HTML: https://mlsanity.com/paper/2510.14861/

## Key facts

- Cited by 9 papers in the map (data through 14 Oct 2026).
- Builds on 2 of its 3 references that are in the map.
- First posted on arXiv 16 Oct 2025.

## Builds on (most cited first, 2 of 2)

- [Alita: Generalist Agent Enabling Scalable Agentic Reasoning with Minimal Predefinition and Maximal Self-Evolution](https://mlsanity.com/paper/2505.20286/) (2025)
- [FineBio: A Fine-Grained Video Dataset of Biological Experiments with Hierarchical Annotation](https://mlsanity.com/paper/2402.00293/) (2024)

## Built on by (most cited first, 9 of 9)

- [Autonomous Research Agents: A Survey of AI Scientists and the Verification Gap](https://mlsanity.com/paper/2608.05179/) (2026)
- [Measuring Mid-2025 LLM-Assistance on Novice Performance in Biology](https://mlsanity.com/paper/2602.16703/) (2026)
- [Qumus: Realization of An Embodied AI Quantum Material Experimentalist](https://mlsanity.com/paper/2605.18407/) (2026)
- [Owl-AuraID 1.0: An Intelligent System for Autonomous Scientific Instrumentation and Scientific Data Analysis](https://mlsanity.com/paper/2603.29828/) (2026)
- [Accelerating Scientific Research with Gemini in the Real-World](https://mlsanity.com/paper/2608.26701/) (2026)
- [A Multi-AI-agent Framework Enabling End-to-end Finite Element Analysis for Solid Mechanics Problems](https://mlsanity.com/paper/2606.00138/) (2026)
- [Science Earth: Towards A Planet-Scale Operating System for AI-Native Scientific Discovery](https://mlsanity.com/paper/2606.01316/) (2026)
- [Harmonizing AI Safety Thresholds](https://mlsanity.com/paper/2607.16112/) (2026)
- [From Seeing to Acting: Smart Glasses as First-Person Intelligence Platforms](https://mlsanity.com/paper/2608.24877/) (2026)

## Abstract (arXiv)

Modern science advances fastest when thought meets action. LabOS represents the first AI co-scientist that unites computational reasoning with physical experimentation through multimodal perception, self-evolving agents, and Extended-Reality(XR)-enabled human-AI collaboration. By connecting multi-model AI agents, smart glasses, and robots, LabOS allows AI to see what scientists see, understand experimental context, and assist in real-time execution. Across applications -- from cancer immunotherapy target discovery to stem-cell engineering and material science -- LabOS shows that AI can move beyond computational design to participation, turning the laboratory into an intelligent, collaborative environment where human and machine discovery evolve together.