SOURCE-LINKED INTELLIGENCE
GitScholar: A Dataset for Predicting AI Research Impact from GitHub Engagement
With the rapid pace of AI research and the hundreds of daily new publications, staying up-to-date with the latest developments has become increasingly difficult. For researchers, quickly identifying impactful work is essential, yet manually reviewing each new publication is impractical. Automated impact prediction methods help address this challenge, usually by combining various information sources available, such as a paper's content or citation history. In this work, we propose using GitHub engagement as an additional source and demonstrate that it provides both a timely and accurate signal.
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Evidence & attribution
- arXiv · AI, language, vision and robotics · 2026-09-22T13:03:31.000Z
First collected: 2026-09-23T04:11:12.117Z. This is not the publication date.