Author

Xiaohong Ji

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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

#machine learning Mar 2026

SpecXMaster Technical Report

This work proposes SpecXMaster, an intelligent framework leveraging Agentic Reinforcement Learning (RL) for NMR molecular spectral interpretation that enables automated extraction of multiplicity information from both 1H and 13C spectra directly from raw FID (free induction decay) data.

Yu-Tang Ge, Ya-Ning Cui, Han-Zheng Li et al. · arXiv.org · 0 citations