Modeling U.S. Supreme Court Briefs with Computational Argumentation

Heng Zheng; Dexter Williams; Bertram Ludäscher

doi:10.3233/FAIA251631

Modeling U.S. Supreme Court Briefs with Computational Argumentation

Heng Zheng
, Dexter Williams
, Bertram Ludäscher

Producción científica: Conference contribution › revisión exhaustiva

Resumen

We show how to represent U.S. Supreme Court briefs as a structured argument model that relies entirely on the briefs' existing structure.

Idioma original	English
Título de la publicación alojada	Legal Knowledge and Information Systems - The Thirty-eighth Annual Conference, JURIX 2025
Editores	Reka Markovich, Luigi Di. Caro, Amon Rapp, Claudio Schifanella
Editorial	IOS Press BV
Páginas	439-441
Número de páginas	3
ISBN (versión digital)	9781643686387
DOI	https://doi.org/10.3233/FAIA251631
Estado	Published - dic 2 2025
Evento	38th International Conference on Legal Knowledge and Information Systems, JURIX 2025 - Turin, Italy Duración: dic 9 2025 → dic 11 2025

Serie de la publicación

Nombre	Frontiers in Artificial Intelligence and Applications
Volumen	416
ISSN (versión impresa)	0922-6389
ISSN (versión digital)	1879-8314

Conference

Conference	38th International Conference on Legal Knowledge and Information Systems, JURIX 2025
País/Territorio	Italy
Ciudad	Turin
Período	12/9/25 → 12/11/25

Nota bibliográfica

Publisher Copyright:
© 2025 The Authors.

Financiación

This work was funded by the 2025 Cardiff University-University of Illinois System Joint Research and Innovation Seed Grants Program. We thank Athena Hatt for suggesting U.S. Supreme Court Briefs. We thank Jodi Schneider and Timothy McPhillips for providing valuable feedback on an earlier draft of this work.

Financiadores
University of Illinois Hospital & Health Sciences System

ASJC Scopus subject areas

Artificial Intelligence

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10.3233/FAIA251631

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Zheng, H., Williams, D., & Ludäscher, B. (2025). Modeling U.S. Supreme Court Briefs with Computational Argumentation. En R. Markovich, L. Di. Caro, A. Rapp, & C. Schifanella (Eds.), Legal Knowledge and Information Systems - The Thirty-eighth Annual Conference, JURIX 2025 (pp. 439-441). (Frontiers in Artificial Intelligence and Applications; Vol. 416). IOS Press BV. https://doi.org/10.3233/FAIA251631

Zheng, Heng ; Williams, Dexter ; Ludäscher, Bertram. / Modeling U.S. Supreme Court Briefs with Computational Argumentation. Legal Knowledge and Information Systems - The Thirty-eighth Annual Conference, JURIX 2025. editor / Reka Markovich ; Luigi Di. Caro ; Amon Rapp ; Claudio Schifanella. IOS Press BV, 2025. pp. 439-441 (Frontiers in Artificial Intelligence and Applications).

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abstract = "We show how to represent U.S. Supreme Court briefs as a structured argument model that relies entirely on the briefs' existing structure.",

keywords = "U.S. Supreme Court, computational argumentation, large language model",

author = "Heng Zheng and Dexter Williams and Bertram Lud{\"a}scher",

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Zheng, H, Williams, D & Ludäscher, B 2025, Modeling U.S. Supreme Court Briefs with Computational Argumentation. En R Markovich, L Di. Caro, A Rapp & C Schifanella (eds.), Legal Knowledge and Information Systems - The Thirty-eighth Annual Conference, JURIX 2025. Frontiers in Artificial Intelligence and Applications, vol. 416, IOS Press BV, pp. 439-441, 38th International Conference on Legal Knowledge and Information Systems, JURIX 2025, Turin, Italy, 12/9/25. https://doi.org/10.3233/FAIA251631

Modeling U.S. Supreme Court Briefs with Computational Argumentation. / Zheng, Heng; Williams, Dexter; Ludäscher, Bertram.
Legal Knowledge and Information Systems - The Thirty-eighth Annual Conference, JURIX 2025. ed. / Reka Markovich; Luigi Di. Caro; Amon Rapp; Claudio Schifanella. IOS Press BV, 2025. p. 439-441 (Frontiers in Artificial Intelligence and Applications; Vol. 416).

Producción científica: Conference contribution › revisión exhaustiva

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Modeling U.S. Supreme Court Briefs with Computational Argumentation

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Nota bibliográfica

Financiación

ASJC Scopus subject areas

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