3 papers
cs.DL2026
Has Scientific Talent Shifted from Depth to Breadth?Evidence across Papers, Knowledge Inputs, Careers, and Teams
Xiaoshn Nee, Haobo Zhong, Xiaomin Ni
Generative artificial intelligence raises a central question for scientific training and organization. Is research shifting from deep specialization toward broad individual knowled…
cs.DL2026
Wavering Oracles: Selective Updating and Correlated Failures in LLMs and Their Implications for Scientific Workflows
Xiaoshn Nee, Haobo Zhong, Xiaomin Ni
Scientific workflows increasingly use repeated queries, multiple models, and interacting agents. Reliability therefore depends on whether models preserve correct conclusions, accep…
cs.DL2026
The Generative AI Gold Rush in Theoretical and Computational Research
Xiaoshn Nee, Haobo Zhong, Xiaomin Ni
Generative AI is changing the production conditions of theoretical and computational research, but its sys tem level effects require measures that separate plat form growth, field…