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May 15, 2026Library Hi Tech News

Think like an LLM: testing three AI citation verification prompts

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Authors

JWJeanine Williamson

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Overview

Randomized trial tests three AI prompts for citation accuracy, suggesting effective strategies.

Key Points

  • The study aims to evaluate the effectiveness of three AI prompts for verifying citation accuracy and analyze their quality based on the CLEAR framework.
  • Tested 45 altered citations from 15 source citations across three prompt strategies: Verify, Correct, and Fit.
  • Analyzed results using quantitative chi-square analysis and the CLEAR framework.
  • Generated a total of 135 prompts for Microsoft CoPilot.
  • The Fit prompt provided the highest accuracy in citation correctness.
  • The Correct prompt generated incorrect citations due to 'corrective hallucinations'.
  • Only the Fit prompt met all criteria of the CLEAR framework: concise, logical, explicit, adaptive, and reflective.

Cite This Study

Jeanine Williamson (2026) studied this question.

synapsesocial.com/papers/6a06b940e7dec685947abce8https://doi.org/10.1108/lhtn-04-2026-0085
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Also Consider

Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context:

  1. 1In the search for the perfect prompt in medical AI queries2025
  2. 2Reducing Hallucinations in Medical AI Through Citation Enforced Prompting in RAG Systems2026 · 3 citations
  3. 3Prompt Design and <scp>AI</scp> Response Quality in University Students’ Academic Learning Tasks2025
  4. 4Prompt engineering in consistency and reliability with the evidence-based guideline for LLMs2024 · 380 citations
  5. 5Better Prompts, Better Usefulness: A Systematic Review and Experimental Evaluation of Structured Prompting Techniques in Large Language Models2026