Measuring Research Convergence in Interdisciplinary Teams Using Large Language Models and Graph Analytics
arXiv 2603.20204•f43bc7c24d360d650ccdeaf7125297f193183b5420e570e3419523de0af97972
AI governanceAI literacyFALCON-AIaccessibilityedge-computingepistemic harmevaluation-benchmarksexpert-personasgenerative AIhuman-in-the-loopinference-efficiencylarge language modelslearning-per-wattmethodologymisinformationmodel-quantisationpeer reviewprompt injectionsocial-science-surveystelework
Paper metadata
- arXiv ID
- 2603.20204
- Version
- Not specified by this published record
- Category
- Computer Science — Computers and Society (cs.CY)
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Evidence and limitations
- Source ID
- arxiv_cs_cy
- Record identifier
- f43bc7c24d360d650ccdeaf7125297f193183b5420e570e3419523de0af97972
- Enrichment time
- 2026-03-24T07:23:54Z
- AI-assisted enrichment
- Yes
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