AI / Research Discovery

The AI Almanac

The AI Almanac: finding the next paper worth reading

Explore the connections between papers and code, and discover the GitScholar research behind The AI Almanac.

The original AI Almanac mark on a warm paper background, framed by research pages and a code notebook.

The AI Almanac brings research discovery and emerging ideas together. Explore the interactive story to see how GitScholar connects papers, authors and code, and browse a real sample from the Almanac.

Explore The AI Almanac.

See the interactive examples and explore the method.

Read the interactive blog

Related publications

2026arXiv

GitScholar: A Dataset for Predicting AI Research Impact from GitHub Engagement

Emilien Guandalino, Lorenz K. Müller, Beatrice Alessandra Motetti, Konstantin Berestizshevsky, Lukas Cavigelli

Research DiscoveryGraph Neural Networks
Abstract summary

GitScholar connects AI papers, citations and timestamped GitHub activity to study early signals of research impact. The dataset links approximately 444,000 repositories with more than 558,000 AI arXiv papers. Experiments investigate whether repository engagement improves the identification of papers that later attract substantial citation attention, beyond academic information alone. Its temporal structure supports retrospective evaluation using information available at a given date.

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