TRACE: Automated Multi-Granularity Analysis of Text Revision

Yu Tian; Katerina Christhilf; Andrew Potter; Jessica Early; Steve Graham; Danielle S. McNamara

TRACE: Automated Multi-Granularity Analysis of Text Revision

Yu Tian, Katerina Christhilf, Andrew Potter, Jessica Early, Steve Graham, Danielle McNamara

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Abstract

This paper introduces TRACE, an automated framework for analyzing textual revisions across drafts. TRACE aligns initial and revised texts and infers interpretable revision operations, such as insert, delete, replace, and move. TRACE supports AI-powered revision analytics, writing assessment, automated feedback, and studies of human–AI writing collaboration.

Anthology ID:: 2026.aimecon-wip.6
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:: 45–51
Language:
URL:: https://aclanthology.org/2026.aimecon-wip.6/
DOI:
Bibkey:
Cite (ACL):: Yu Tian, Katerina Christhilf, Andrew Potter, Jessica Early, Steve Graham, and Danielle McNamara. 2026. TRACE: Automated Multi-Granularity Analysis of Text Revision. In Proceedings of the Artificial Intelligence in Measurement and Education Conference (AIME-Con): Works in Progress, pages 45–51, Wyndham Grand Pittsburgh Downtown, Pittsburgh, Pennsylvania, United States. National Council on Measurement in Education (NCME).
Cite (Informal):: TRACE: Automated Multi-Granularity Analysis of Text Revision (Tian et al., AIME-Con 2026)
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PDF:: https://aclanthology.org/2026.aimecon-wip.6.pdf

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@inproceedings{tian-etal-2026-trace,
    title = "{TRACE}: Automated Multi-Granularity Analysis of Text Revision",
    author = "Tian, Yu  and
      Christhilf, Katerina  and
      Potter, Andrew  and
      Early, Jessica  and
      Graham, Steve  and
      McNamara, Danielle",
    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.6/",
    pages = "45--51",
    ISBN = "979-8-9983004-1-7",
    abstract = "This paper introduces TRACE, an automated framework for analyzing textual revisions across drafts. TRACE aligns initial and revised texts and infers interpretable revision operations, such as insert, delete, replace, and move. TRACE supports AI-powered revision analytics, writing assessment, automated feedback, and studies of human{--}AI writing collaboration."
}

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%0 Conference Proceedings
%T TRACE: Automated Multi-Granularity Analysis of Text Revision
%A Tian, Yu
%A Christhilf, Katerina
%A Potter, Andrew
%A Early, Jessica
%A Graham, Steve
%A McNamara, Danielle
%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 tian-etal-2026-trace
%X This paper introduces TRACE, an automated framework for analyzing textual revisions across drafts. TRACE aligns initial and revised texts and infers interpretable revision operations, such as insert, delete, replace, and move. TRACE supports AI-powered revision analytics, writing assessment, automated feedback, and studies of human–AI writing collaboration.
%U https://aclanthology.org/2026.aimecon-wip.6/
%P 45-51

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Markdown (Informal)

[TRACE: Automated Multi-Granularity Analysis of Text Revision](https://aclanthology.org/2026.aimecon-wip.6/) (Tian et al., AIME-Con 2026)

TRACE: Automated Multi-Granularity Analysis of Text Revision (Tian et al., AIME-Con 2026)

ACL

Yu Tian, Katerina Christhilf, Andrew Potter, Jessica Early, Steve Graham, and Danielle McNamara. 2026. TRACE: Automated Multi-Granularity Analysis of Text Revision. In Proceedings of the Artificial Intelligence in Measurement and Education Conference (AIME-Con): Works in Progress, pages 45–51, Wyndham Grand Pittsburgh Downtown, Pittsburgh, Pennsylvania, United States. National Council on Measurement in Education (NCME).