Tootfinder

With #openalex being mature enough, I have finally completed #degoogling my website 🥳
https://

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Excited to see the rewrite of the @… backend now in public beta! If you use Google Scholar, Scopus, of Web of Science you should really checkout this open (source & data) alternative.
https://blog.openalex.org/openalex-rewrite-enters-beta-🎉/
COI: I volunteer on the board of OpenAlex because they build awesome things

Wow, I nearly missed that announcement! The CNRS (the main national research agency of France, that happens to be one of Europe's largest) will stop paying for Clarivate's Web of Science and instead turns to open databases like OpenAlex!
https://www.cnrs.fr/en/update/cnrs-breaking-free-web-science

Trajectories and Comparative Analysis of Global Countries Dominating AI Publications, 2000-2025
Jason Hung
https://arxiv.org/abs/2509.25298 https://arxiv.o…

Trajectories and Comparative Analysis of Global Countries Dominating AI Publications, 2000-2025
This study investigates the shifting global dynamics of Artificial Intelligence (AI) research by analysing the trajectories of countries dominating AI publications between 2000 and 2025. Drawing on the comprehensive OpenAlex dataset and employing fractional counting to avoid double attribution in co-authored work, the research maps the relative shares of AI publications across major global players. The analysis reveals a profound restructuring of the international AI research landscape. The US …

Utilizing Modern Large Language Models (LLM) for Financial Trend Analysis and Digest Creation
Andrei Lazarev, Dmitrii Sedov
https://arxiv.org/abs/2510.01225 https://

Utilizing Modern Large Language Models (LLM) for Financial Trend Analysis and Digest Creation
The exponential growth of information presents a significant challenge for researchers and professionals seeking to remain at the forefront of their fields and this paper introduces an innovative framework for automatically generating insightful financial digests using the power of Large Language Models (LLMs), specifically Google's Gemini Pro. By leveraging a combination of data extraction from OpenAlex, strategic prompt engineering, and LLM-driven analysis, we demonstrate the automated exampl…

A Living Review Pipeline for AI/ML Applications in Accelerator Physics
Adnan Ghribi
https://arxiv.org/abs/2510.09376 https://arxiv.org/pdf/2510.09376

A Living Review Pipeline for AI/ML Applications in Accelerator Physics
We present an open-source pipeline for generating a \emph{living review} of artificial intelligence (AI) and machine learning (ML) applications in accelerator physics and technologies. Traditional review articles provide static snapshots that are quickly outdated by the rapid pace of research. The presented system automatically harvests publications from multiple bibliographic sources (arXiv, InspireHEP, HAL, OpenAlex, Crossref, and Springer), deduplicates entries, applies semantic filtering to…