LLM as Investigator and Judge in Pairwise Comparisons for Item Parameter Modeling

Brian Harrold; Vincent Fakiyesi; Maria D’Brot; Susan Lottridge; Justin Barber; Michael Hemenway

LLM as Investigator and Judge in Pairwise Comparisons for Item Parameter Modeling

Brian Harrold, Vincent Fakiyesi, Maria D’Brot, Susan Lottridge, Justin Barber, Michael Hemenway

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Abstract

This study synthesizes feature-based and pairwise-comparison approaches to item parameter modeling by using an LLM as an investigator of item characteristics and a judge of relative item parameters. The proposed framework aims to improve recovery of item parameter rankings and predictions while providing insight into factors associated with the parameters.

Anthology ID:: 2026.aimecon-wip.52
Volume:: Proceedings of the Artificial Intelligence in Measurement and Education Conference (AIME-Con): Works in Progress
Month:: October
Year:: 2026
Address:: Wyndham Grand Pittsburgh Downtown, Pittsburgh, Pennsylvania, United States
Editors:: Joshua Wilson, Christopher Ormerod, Magdalen Beiting-Parrish
Venue:: AIME-Con
SIG:
Publisher:: National Council on Measurement in Education (NCME)
Note:
Pages:: 405–415
Language:
URL:: https://aclanthology.org/2026.aimecon-wip.52/
DOI:
Bibkey:
Cite (ACL):: Brian Harrold, Vincent Fakiyesi, Maria D’Brot, Susan Lottridge, Justin Barber, and Michael Hemenway. 2026. LLM as Investigator and Judge in Pairwise Comparisons for Item Parameter Modeling. In Proceedings of the Artificial Intelligence in Measurement and Education Conference (AIME-Con): Works in Progress, pages 405–415, Wyndham Grand Pittsburgh Downtown, Pittsburgh, Pennsylvania, United States. National Council on Measurement in Education (NCME).
Cite (Informal):: LLM as Investigator and Judge in Pairwise Comparisons for Item Parameter Modeling (Harrold et al., AIME-Con 2026)
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PDF:: https://aclanthology.org/2026.aimecon-wip.52.pdf

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Preformatted

@inproceedings{harrold-etal-2026-llm,
    title = "{LLM} as Investigator and Judge in Pairwise Comparisons for Item Parameter Modeling",
    author = "Harrold, Brian  and
      Fakiyesi, Vincent  and
      D{'}Brot, Maria  and
      Lottridge, Susan  and
      Barber, Justin  and
      Hemenway, Michael",
    editor = "Wilson, Joshua  and
      Ormerod, Christopher  and
      Beiting-Parrish, Magdalen",
    booktitle = "Proceedings of the Artificial Intelligence in Measurement and Education Conference ({AIME}-Con): Works in Progress",
    month = oct,
    year = "2026",
    address = "Wyndham Grand Pittsburgh Downtown, Pittsburgh, Pennsylvania, United States",
    publisher = "National Council on Measurement in Education (NCME)",
    url = "https://aclanthology.org/2026.aimecon-wip.52/",
    pages = "405--415",
    ISBN = "979-8-9983004-1-7",
    abstract = "This study synthesizes feature-based and pairwise-comparison approaches to item parameter modeling by using an LLM as an investigator of item characteristics and a judge of relative item parameters. The proposed framework aims to improve recovery of item parameter rankings and predictions while providing insight into factors associated with the parameters."
}

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Download as File

%0 Conference Proceedings
%T LLM as Investigator and Judge in Pairwise Comparisons for Item Parameter Modeling
%A Harrold, Brian
%A Fakiyesi, Vincent
%A D’Brot, Maria
%A Lottridge, Susan
%A Barber, Justin
%A Hemenway, Michael
%Y Wilson, Joshua
%Y Ormerod, Christopher
%Y Beiting-Parrish, Magdalen
%S Proceedings of the Artificial Intelligence in Measurement and Education Conference (AIME-Con): Works in Progress
%D 2026
%8 October
%I National Council on Measurement in Education (NCME)
%C Wyndham Grand Pittsburgh Downtown, Pittsburgh, Pennsylvania, United States
%@ 979-8-9983004-1-7
%F harrold-etal-2026-llm
%X This study synthesizes feature-based and pairwise-comparison approaches to item parameter modeling by using an LLM as an investigator of item characteristics and a judge of relative item parameters. The proposed framework aims to improve recovery of item parameter rankings and predictions while providing insight into factors associated with the parameters.
%U https://aclanthology.org/2026.aimecon-wip.52/
%P 405-415

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Markdown (Informal)

[LLM as Investigator and Judge in Pairwise Comparisons for Item Parameter Modeling](https://aclanthology.org/2026.aimecon-wip.52/) (Harrold et al., AIME-Con 2026)

LLM as Investigator and Judge in Pairwise Comparisons for Item Parameter Modeling (Harrold et al., AIME-Con 2026)

ACL

Brian Harrold, Vincent Fakiyesi, Maria D’Brot, Susan Lottridge, Justin Barber, and Michael Hemenway. 2026. LLM as Investigator and Judge in Pairwise Comparisons for Item Parameter Modeling. In Proceedings of the Artificial Intelligence in Measurement and Education Conference (AIME-Con): Works in Progress, pages 405–415, Wyndham Grand Pittsburgh Downtown, Pittsburgh, Pennsylvania, United States. National Council on Measurement in Education (NCME).