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Peishan Li

Publications and source records attributed to Peishan Li.

3 recordsLinked to original sources
arXiv2025

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

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.

cs.AI↗
arXiv2025

Sufficient conditions for the variation of toughness under the distance spectral in graphs involving minimum degree

The concept of graph toughness was first introduced in 1973. In 1995, scholars first explored the lower bound of the toughness of connected d-regular graphs with respect to d and the second largest eigenvalue of the adjacency matrix. The concept of the variation of toughness was first introduced in 1988. The variation of toughness is defined as tau(G) = min{|S|/(c(G-S)-1)}. In 2025, Chen, Fan, and Lin provided sufficient conditions for a graph to be t-tough in terms of the minimum degree and the distance spectral radius. Inspired by this, we propose a sufficient condition for a graph to be tau-tough in terms of minimum degree and distance spectral radius, and provide the corresponding proof, where |S| and c(G-S)-1 are mutually divisible.

math.CO↗