arXiv:2607. 21327v1 Announce Type: cross Abstract: Bibliometric indicators - citation counts, h-indexes, co-authorship networks - have long anchored science, technology, and innovation (STI) analytics, yet suffer from temporal lag, semantic shallowness, and an inability to capture the non-linear dynamics of contemporary knowledge ecosystems.
By Muhsen Hammoud
arXiv:2605. 18661v2 Announce Type: replace Abstract: AI-assisted research is crossing a threshold: fully automated systems can now generate research papers for as little as $15, while long-horizon agents can execute experiments, draft manuscripts, and simulate critique with minimal human input.
By Lingdong Kong, Xian Sun, Wei Chow, Linfeng Li, Kevin Qinghong Lin, Xuan Billy Zhang, Song Wang, Rong Li, Qing Wu, Wei Gao, Yingshuo Wang, Shaoyuan Xie, Jiachen Liu, Leigang Qu, Shijie Li, Lai Xing Ng, Benoit R. Cottereau, Ziwei Liu, Tat-Seng Chua, Wei Tsang Ooi
arXiv:2607. 03233v1 Announce Type: cross Abstract: The rapid growth of publicly available digital information has rendered manual open-source intelligence (OSINT) analysis insufficient for modern intelligence, cybersecurity, and cyber investigation.
By Eduardo Almeida Palmieri, Mohamed Chahine Ghanem, Dipo Dunsin, Zubair Baig, Ed de Quincey, Kim-Kwang Raymond Choo
arXiv:2606. 19630v1 Announce Type: new Abstract: The March 2020 INCOSE INSIGHT special issue on AI and Systems Engineering (SE) became the most downloaded issue in the publication's history and launched a research community that now draws over 250 registrants to its annual workshop.
By H. Sinan Bank, Daniel R. Herber, Thomas Bradley
arXiv:2607. 15164v1 Announce Type: new Abstract: Artificial intelligence is transforming scientific research - not merely as a more powerful instrument, but as an autonomous participant in the research cycle itself.
By Emmanuel Jeannot
The paper proposes a new interdisciplinary field called Cognitive Infrastructure Studies (CIS) to examine how AI systems act as invisible, foundational cognitive infrastructures that shape what people can know and do in digital societies. It argues that these infrastructures, through anticipatory personalization and adaptive invisibility, automate relevance judgments and shift epistemic agency to non‑human systems. CIS offers methodological tools, such as infrastructure breakdown experiments, to uncover the hidden cognitive dependencies created by AI preprocessing across individual, collective, and societal levels.
By Giuseppe Riva