arXiv:2609.14425v1 Announce Type: cross
Abstract: Generative artificial intelligence raises a central question for scientific training and organization. Is research shifting from deep specialization...
By Xiaoshn Nee, Haobo Zhong, Xiaomin Ni
arXiv:2601. 15485v3 Announce Type: replace-cross Abstract: Federal research funding shapes the direction, diversity, and impact of the US scientific enterprise.
By Yifan Qian, Zhe Wen, Alexander C. Furnas, Yue Bai, Erzhuo Shao, Dashun Wang
arXiv:2607. 16989v1 Announce Type: cross Abstract: Introduction.
By Mohammad Arvan, Amber E. Osterholt, Bailee Rue, Yuvaneswaren Ramakrishnan Sureshbabu, Krishna Riteshkumar Patel, Rebecca T. Feinstein, Bethany C. Bray, Niranjan S. Karnik
arXiv:2506. 17467v2 Announce Type: replace-cross Abstract: Large language models (LLMs) have shown significant potential to change how we write, communicate, and create, leading to rapid adoption across society.
By Weixin Liang
The paper "AI in Science: Early Insights" analyzes AI’s impact on scientific work using data from 15 million Gemini interactions, 2,600 specialized AI models, and a survey of 600 scientists. It finds widespread AI adoption, complementary use of large language models and specialized tools, significant productivity gains of about seven hours per week, and a shift in research bottlenecks toward hypothesis backlog and verification needs. The study suggests AI can boost scientific productivity but its full effect depends on addressing new downstream challenges.
By Mihai Codreanu, Alex Imas, Juan Mateos-Garcia, Joseph Emmens, Evalyne Muiruri, Arthur Turrell, Julian Jacobs, Atoosa Kasirzadeh, Ana Trisovic, Yiyuan Chen, Tanya Rodchenko, Catherine Pollard, Scott Strand, Daniel Rock, Zanna Iscenko, Fabien Curto Millet, Neil Thompson, James Manyika
The paper introduces SciUtopia, a closed‑loop large‑language‑model simulation framework that models the evolving academic research ecosystem, including research direction, collaboration, publication, peer review, funding, and researcher attrition. Running 61 simulation worlds, the system simulates over 40,000 researchers and 1.2 million LLM‑generated peer reviews, revealing that rejection‑driven resubmission increases reviewer burden, cautious exploration balances citation impact with career success, and resource inequality can arise without early‑funding advantage.
By Yiqiao Jin, Yiyang Wang, Lucheng Fu, Bing He, Siheng Xiong, Yijia Xiao, B. Aditya Prakash, Josiah Hester, Srijan Kumar, James Evans, Jindong Wang