Since the 1990s, advancements in big data and information technology have increasingly driven data-centric research in the field of Library and Information Science (LIS). To assess the influence of this data-driven research paradigm on the LIS discipline, this study conducts a fine-grained analysis to uncover the evolutionary trends of research methods within the domain.
arXiv:2607. 20328v1 Announce Type: cross Abstract: This study empirically analyzed generative AI as an emerging discovery pathway to academic library resources.
By Hae Min Kim, Stacy Stanislaw
The global development of Library and Information Science (LIS) is influenced by various factors such as the economy, society, culture, discipline, tradition, and more. Consequently, the research methods of LIS vary greatly among countries.
arXiv:2511. 14007v3 Announce Type: replace-cross Abstract: Artificial intelligence (AI) raises expectations of substantial increases in rates of technological progress, but such anticipations are often not connected to detailed ground-level studies of AI use in innovation processes.
By John P. Nelson, Olajide Olugbade, Philip Shapira, Justin B. Biddle
arXiv:2608. 09964v1 Announce Type: cross Abstract: The Brazilian Conference on Intelligent Systems (BRACIS) is the main national venue for Artificial Intelligence research in Brazil, hosted by the Brazilian Computer Society since 2012 and publishing work from institutions across the country.
By Thales Sales Almeida, Giovana Kerche Bon\'as, Thiago Laitz, Jo\~ao Guilherme Alves Santos, Hugo Abonizio, Roseval Malaquias Junior, Marcos Piau, Celio Larcher, Ramon Pires, Rodrigo Nogueira
arXiv:2607. 16845v1 Announce Type: new Abstract: Scientists at European XFEL conduct experiments that generate very large and complex datasets.
By Tim Fuchs, Luca Gelisio, Steffen Hauf, Walid Maalej
arXiv:2607. 17242v1 Announce Type: cross Abstract: Pretrained machine learning (ML) models help developers build ML-intensive software systems without training models from scratch.
By Md Erfan, Ahmed Ryan, Md Rayhanur Rahman
arXiv:2606. 31366v1 Announce Type: cross Abstract: Driven by high-throughput experimentation, computational modeling, and artificial intelligence (AI), materials data has expanded at an unprecedented rate.
By Chenyao Ma, Di Zhang, Weibo Gong, Wei Du, Rui Su, Yuhang Chen, Kan Xu, Huan Gu, Limin Li, Piao Ma, Zhenghao Li, Hao Li
arXiv:2606. 05222v1 Announce Type: cross Abstract: Artificial intelligence (AI) has been applied across educational contexts to support learning.
By Luis P. Prieto, Juan I. Asensio-P\'erez, Mar\'ia Jes\'us Rodr\'iguez-Triana, Mohamed Saban, Yannis Dimitriadis
arXiv:2509. 02581v2 Announce Type: replace-cross Abstract: Despite the growing availability of tools designed to support scholarly knowledge extraction and organization, many researchers still rely on manual methods, sometimes due to unfamiliarity with existing technologies or limited access to domain-adapted solutions.
By Azanzi Jiomekong, Hande K\"u\c{c}\"uk McGinty, Keith G. Mills, Allard Oelen, Enayat Rajabi, Harry McElroy, Antrea Christou, Anmol Saini, Janice Anta Zebaze, Hannah Kim, Anna M. Jacyszyn, Gollam Rabby, Dirk Betz, Claudia Biniossek, Sanju Tiwari, S\"oren Auer
arXiv:2606. 16974v3 Announce Type: replace Abstract: The reproducibility crisis has directed the AI research community toward improving documentation practices.
By Kevin L Coakley, Thijs Snelleman, Holger Hoos, Odd Erik Gundersen
arXiv:2607. 00558v1 Announce Type: cross Abstract: As Artificial Intelligence(AI)-based applications take off, a clear understanding of AI patterns can uplift the quality of AI applications.
By Srinath Perera, Hasinthaka Piyumal, Frank Leymann, Rania Khalaf