@inproceedings{przybyla-2025-starling,
title = "{STARLING} at {TSAR} 2025 Shared Task Leveraging Alternative Generations for Readability Level Adjustment in Text Simplification",
author = "Przyby{\l}a, Piotr",
editor = "Shardlow, Matthew and
Alva-Manchego, Fernando and
North, Kai and
Stodden, Regina and
Saggion, Horacio and
Khallaf, Nouran and
Hayakawa, Akio",
booktitle = "Proceedings of the Fourth Workshop on Text Simplification, Accessibility and Readability (TSAR 2025)",
month = nov,
year = "2025",
address = "Suzhou, China",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2025.tsar-1.12/",
pages = "155--159",
ISBN = "979-8-89176-176-6",
abstract = "Readability adjustment is crucial in text simplification, as it allows to generate language appropriate to the needs of a particular group of readers. Here we present a method for simplifying a text fragment that aims for a given CEFR level, e.g. A2 or B1. The proposed approach combines prompted large language model with sentence-level adjustment of difficulty level. The work is evaluated within the framework of TSAR 2025 shared task, showing a trade-off between precise readability adjustment and faithful meaning preservation."
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<abstract>Readability adjustment is crucial in text simplification, as it allows to generate language appropriate to the needs of a particular group of readers. Here we present a method for simplifying a text fragment that aims for a given CEFR level, e.g. A2 or B1. The proposed approach combines prompted large language model with sentence-level adjustment of difficulty level. The work is evaluated within the framework of TSAR 2025 shared task, showing a trade-off between precise readability adjustment and faithful meaning preservation.</abstract>
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%0 Conference Proceedings
%T STARLING at TSAR 2025 Shared Task Leveraging Alternative Generations for Readability Level Adjustment in Text Simplification
%A Przybyła, Piotr
%Y Shardlow, Matthew
%Y Alva-Manchego, Fernando
%Y North, Kai
%Y Stodden, Regina
%Y Saggion, Horacio
%Y Khallaf, Nouran
%Y Hayakawa, Akio
%S Proceedings of the Fourth Workshop on Text Simplification, Accessibility and Readability (TSAR 2025)
%D 2025
%8 November
%I Association for Computational Linguistics
%C Suzhou, China
%@ 979-8-89176-176-6
%F przybyla-2025-starling
%X Readability adjustment is crucial in text simplification, as it allows to generate language appropriate to the needs of a particular group of readers. Here we present a method for simplifying a text fragment that aims for a given CEFR level, e.g. A2 or B1. The proposed approach combines prompted large language model with sentence-level adjustment of difficulty level. The work is evaluated within the framework of TSAR 2025 shared task, showing a trade-off between precise readability adjustment and faithful meaning preservation.
%U https://aclanthology.org/2025.tsar-1.12/
%P 155-159
Markdown (Informal)
[STARLING at TSAR 2025 Shared Task Leveraging Alternative Generations for Readability Level Adjustment in Text Simplification](https://aclanthology.org/2025.tsar-1.12/) (Przybyła, TSAR 2025)
ACL