ScholarCatalyst: A Benchmark for Retrieving Papers That Inspire New Research
- Published
- Source
- arXiv
- Paper number
- 1145
- Field
- AI / General
- arXiv ID
- 2610.02202
Key points
- The authors constructed 894 early-stage research questions based on judgments from 184 researchers.
- The study reported that search agents retrieved 42% of the needed papers in the top 20 results, compared with 48% for semantic similarity retrieval.
- The study found that 43.6% of the papers judged useful for subfield-specific questions were absent from the source studies’ reference lists.
- The analysis indicated that getting useful candidates into the search results mattered more than reading the candidate papers at greater length.
Paper links
External research summaries. These are not HDATF publications or measured product results.