5 papers
Toward a Community Roadmap for High Energy Physics and Artificial Intelligence in China and Beyond
Tianji Cai, Ke Li, Teng Li
Artificial Intelligence (AI) is rapidly transforming scientific research and has become central to many data-intensive disciplines. High Energy Physics (HEP), with its vast data vo…
HepScript: A Dual-Use DSL for Human-AI Collaborative Data Analysis Workflows in High-Energy Physics
Junkun Jiao, Tong Liu, Ke Li +6
The escalating data scale in High-Energy Physics (HEP) fuels a growing aspiration for higher analytical efficiency. While Large Language Models (LLMs) offer a path toward automatio…
Dr.Sai: An agentic AI for real-world physics analysis at BESIII
Mingfeng He, Fayu Jiang, Junkun Jiao +16
High Energy Physics (HEP) experiments like BESIII produce petabyte-scale data. Extracting physics results requires complex workflows (simulation, reconstruction, statistical analys…
From decay to cluster decay: an extreme case of transfer learning
Yinu Zhang, Zhiyi Li, Kele Li +2
When training data are limited, data-driven models are especially vulnerable to optimization-related fluctuations from random initialization and to sampling-induced bias from insuf…
AI Agents, Language, Deep Learning and the Next Revolution in Science
Ke Li, Beijiang Liu, Bruce Mellado +2
Modern science is reaching a critical inflection point. Instruments across disciplines, from particle physics and astronomy to genomics and climate modeling, now produce data of su…