Large Knowledge Model: From Papers to a Scientific Reasoning Landscape
Yuan Huang, Si-Han Hu, Hong-Yu Gu et al.
· 1 citation
3 papers indexed here
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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
The Large Knowledge Model is proposed, a growing, agent-native knowledge foundation that provides a general representation of scientific knowledge across disciplines and an agent-native, reasoning-aware scientific retrieval system that retrieves claims together with their reasoning chains and sources, enabling agents t...
Yuan Huang, Si-Han Hu, Hong-Yu Gu et al.
· 0 citations