Measuring Research Convergence in Interdisciplinary Teams Using Large Language Models and Graph Analytics
2026-03-24T07:23:54Z•f43bc7c24d360d650ccdeaf7125297f193183b5420e570e3419523de0af97972
AI governanceAI literacyFALCON-AIaccessibilityedge-computingepistemic harmevaluation-benchmarksexpert-personasgenerative AIhuman-in-the-loopinference-efficiencylarge language modelslearning-per-wattmethodologymisinformationmodel-quantisationpeer reviewprompt injectionsocial-science-surveystelework
What happened
Collection of recent arXiv papers (Mar 24 2026) on LLM applications, evaluation, governance, and socio-technical impacts. Key contributions include: an AI+graph framework to map research convergence in interdisciplinary teams; empirical work on teacher–chatbot interactions and design scaffolds for block-based programming; governance analysis of GenAI in peer review highlighting risks (epistemic harm, over-standardization, prompt injection) and recommending human-only evaluative judgment; a validated FALCON-AI faculty AI literacy scale; Phase-Aware Coherence Detection (PACD) to reduce backfire/
Why it matters
A reviewed impact interpretation has not been published for this record.
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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