Large Knowledge Model: From Papers to a Scientific Reasoning Landscape
Yuan Huang, Si-Han Hu, Hong-Yu Gu et al.
· 0 citations
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Open access
2026
Bohrium + SciMaster: Building the infrastructure and ecosystem for agentic science at scale
AI agents are emerging as a practical way to run multi-step scientific workflows that interleave reasoning, tool use, and verification. Scaling such agentic science remains difficult because workflows are hard to observe and reproduce, many scientific tools and laboratory systems are not agent-ready, and execution trac...
Lin-Feng Zhang, Si-Heng Chen, Yu-Zhu Cai et al.
· AI Plus · 0 citations
Large Knowledge Model: A Knowledge Foundation for Agentic Science at Scale
Agentic science envisions many autonomous agents investigating concurrently while building on a shared, evolving body of scientific knowledge. This requires a knowledge foundation that supports high-concurrency access, preserves traceable and reusable reasoning, and grows incrementally. We propose the Large Knowledge M...
Yuan Huang, Si-Han Hu, Hong-Yu Gu et al.
· 0 citations