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New framework uses LLMs to detect fabricated academic citations

By PulseAugur Editorial · [1 sources] ·

Researchers have developed a new framework called the Fabrication Severity Stack (FSS) to identify fabricated citations in academic work. This three-tiered system categorizes citation fabrications based on their detection difficulty, ranging from completely non-existent references to more subtle misattributions. The proposed method utilizes a staged heuristic workflow that can be implemented using standard large language model interfaces, offering a practical, zero-cost solution for educators to integrate reference verification into dissertation and report assessments. Preliminary testing showed that this approach could effectively flag non-existent references and detect some metadata corruption. AI

IMPACT Provides a zero-cost method for educators to combat AI-generated academic dishonesty.

RANK_REASON Academic paper proposing a new framework and methodology. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.AI →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

New framework uses LLMs to detect fabricated academic citations

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Academic paper proposing a new framework and methodology. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. arXiv cs.AI TIER_1 English(EN) · Hazrat Ali, Mohamed Elawady ·

    Zero-Cost Detection of Fabricated Citations: A Staged Heuristic Approach for Computing Dissertation Assessment

    arXiv:2610.28649v1 Announce Type: cross Abstract: Generative AI's growing role in academic writing has driven a rise in fabricated references across dissertations and student reports. We present the Fabrication Severity Stack (FSS), a three-tiered framework classifying citation f…

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