Artificial Intelligence in Scientific Publishing
A key problem facing science publishing is the firehose of data. For example, reading all monthly submissions to arXiv would take 8 years, and all papers on COVID-19 would take 150 years. To address this problem and increase the accessibility of research, we launched a platform to experiment with AI tools for data processing, including:
• AI summarization of articles
• AI-guided peer review (matching of papers and referees)
• Automatic detection of low-quality or fraudulent content
• Decomposition of papers into facts
• Similarity and contradiction indices
• Ontology (knowledge graphs) of papers enriched with AI analysis of data
We deploy these AI tools at ScienceCast.org, which is run by the company ScienceCast in Baltimore, MD.
ScienceCast pilots
•AI writes summaries of preprints in bioRxiv trials
•Collaboration with ElevenLabs & arXiv Generates Digestible Videos for Open Access Research
•ArXivLabs collaboration links researchers’ videos to their arXiv papers
Special issues
We ran a few special issues at Annals of Physics dedicated to the life and work of several seminal scientists including
• Special issue on Philip W. Anderson
• Eliashberg theory at 60: Strong-coupling superconductivity
• Special issue in memory of Prof. Konstantin B. Efetov