New framework proposes "Traceable Scholarship" for AI-assisted research

A new paper proposes "Traceable Scholarship" as a crucial standard for AI-assisted humanistic research, aiming to combat the risk of generative AI producing fluent but unsubstantiated text. The proposed framework introduces concepts like page anchors, dual page numbers, and citation-first generation to ensure that AI-generated scholarly content remains verifiable and refutable. A reference implementation called AIH-Infra, comprising document structuring, a traceable knowledge base, and an agent gateway, is presented to support these traceability mechanisms. AI

IMPACT Establishes a normative standard for AI-assisted scholarship, aiming to maintain research integrity and verifiability.

RANK_REASON The item is an academic paper proposing a new framework and methodology for AI-assisted research. [lever_c_demoted from research: ic=1 ai=1.0]

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