Evaluating Llama 3 for Text Simplification: A Study on Wikipedia Lead Sections

• Tipo: Artigo em Livro de Atas de Conferência Internacional
• Data: 2025

Autores

Rodrigues, JF (Autor) Outra; Cardoso, HL (Autor) Outra; Carla Teixeira Lopes (Autor) FEUP

Ata de Conferência Internacional

Título: Companion Proceedings of the ACM on Web Conference 2025, WWW 2025, Sydney, NSW, Australia, 28 April 2025 - 2 May 2025

Páginas: 1273-1277

34th ACM Web Conference, WWW Companion 2025

Sydney, 28 April 2025 through 2 May 2025

Indexação

ISI Web of Knowledge - 0 Citações

Scopus - 1 Citação

Outras Informações

ID Authenticus: P-018-Z2Z

DOI: 10.1145/3701716.3715467

Abstract (EN): Text simplification converts complex text into simpler language, improving readability and comprehension. This study evaluates the effectiveness of open-source large language models for text simplification across various categories. We created a dataset of 66,620 lead section pairs from English and Simple English Wikipedia, spanning nine categories, and tested Llama 3 for text simplification. We assessed its output for readability, simplicity, and meaning preservation. Results show improved readability, with simplification varying by category. Texts on Time were the most shortened, while Leisurerelated texts had the greatest reduction of words/characters and syllables per sentence. Meaning preservation was most effective for the Objects and Education categories.

Idioma: Inglês

Tipo (Avaliação Docente): Científica

Nº de páginas: 5