@inproceedings{paula-camilo-junior-2024-evaluating,
title = "Evaluating the Simplification of {B}razilian Legal Rulings in {LLM}s Using Readability Scores as a Target",
author = "Paula, Antonio Flavio and
Camilo-Junior, Celso",
editor = "Shardlow, Matthew and
Saggion, Horacio and
Alva-Manchego, Fernando and
Zampieri, Marcos and
North, Kai and
{\v{S}}tajner, Sanja and
Stodden, Regina",
booktitle = "Proceedings of the Third Workshop on Text Simplification, Accessibility and Readability (TSAR 2024)",
month = nov,
year = "2024",
address = "Miami, Florida, USA",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2024.tsar-1.12",
pages = "117--125",
abstract = "Legal documents are often characterized by complex language, including jargon and technical terms, making them challenging for Natural Language Processing (NLP) applications. We apply the readability-controlled text modification task with an emphasis on legal texts simplification. Additionally, our work explores an evaluation based on the comparison of word complexity in the documents using Zipf scale, demonstrating the models{'} ability to simplify text according to the target readability scores, while also identifying a limit to this capability. Our results with Llama-3 and Sabi{\'a}-2 show that while the complexity score decreases with higher readability targets, there is a trade-off with reduced semantic similarity.",
}
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<abstract>Legal documents are often characterized by complex language, including jargon and technical terms, making them challenging for Natural Language Processing (NLP) applications. We apply the readability-controlled text modification task with an emphasis on legal texts simplification. Additionally, our work explores an evaluation based on the comparison of word complexity in the documents using Zipf scale, demonstrating the models’ ability to simplify text according to the target readability scores, while also identifying a limit to this capability. Our results with Llama-3 and Sabiá-2 show that while the complexity score decreases with higher readability targets, there is a trade-off with reduced semantic similarity.</abstract>
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%0 Conference Proceedings
%T Evaluating the Simplification of Brazilian Legal Rulings in LLMs Using Readability Scores as a Target
%A Paula, Antonio Flavio
%A Camilo-Junior, Celso
%Y Shardlow, Matthew
%Y Saggion, Horacio
%Y Alva-Manchego, Fernando
%Y Zampieri, Marcos
%Y North, Kai
%Y Štajner, Sanja
%Y Stodden, Regina
%S Proceedings of the Third Workshop on Text Simplification, Accessibility and Readability (TSAR 2024)
%D 2024
%8 November
%I Association for Computational Linguistics
%C Miami, Florida, USA
%F paula-camilo-junior-2024-evaluating
%X Legal documents are often characterized by complex language, including jargon and technical terms, making them challenging for Natural Language Processing (NLP) applications. We apply the readability-controlled text modification task with an emphasis on legal texts simplification. Additionally, our work explores an evaluation based on the comparison of word complexity in the documents using Zipf scale, demonstrating the models’ ability to simplify text according to the target readability scores, while also identifying a limit to this capability. Our results with Llama-3 and Sabiá-2 show that while the complexity score decreases with higher readability targets, there is a trade-off with reduced semantic similarity.
%U https://aclanthology.org/2024.tsar-1.12
%P 117-125
Markdown (Informal)
[Evaluating the Simplification of Brazilian Legal Rulings in LLMs Using Readability Scores as a Target](https://aclanthology.org/2024.tsar-1.12) (Paula & Camilo-Junior, TSAR 2024)
ACL