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20232026
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cs.CL2026

Reinforcement Learning for improving Large Language Models' Catalan text simplification capabilities

Arnau Ayguadé Domingo, Stefan Bott, Horacio Saggion

Although automatic text simplification (ATS) is critical for accessibility, its progress has not matched the rapid evolution of broader natural language processing techniques. This…

cs.CL2026

SimpCue: Cue-Based Prompting for Multilingual Text Simplification

Mehrzad Tareh, Horacio Saggion, Stefan Bott

Text simplification aims to make complex texts easier to understand while preserving their original meaning. Recent large language models can perform simplification through prompti…

cs.CL2025

Towards Trustworthy Lexical Simplification: Exploring Safety and Efficiency with Small LLMs

Akio Hayakawa, Stefan Bott, Horacio Saggion

Despite their strong performance, large language models (LLMs) face challenges in real-world application of lexical simplification (LS), particularly in privacy-sensitive and resou…

cs.CL2025

UniversalCEFR: Enabling Open Multilingual Research on Language Proficiency Assessment

Joseph Marvin Imperial, Abdullah Barayan, Regina Stodden +16

We introduce UniversalCEFR, a large-scale multilingual and multidimensional dataset of texts annotated with CEFR (Common European Framework of Reference) levels in 13 languages. To…

cs.CL2024

Lexical Complexity Prediction and Lexical Simplification for Catalan and Spanish: Resource Creation, Quality Assessment, and Ethical Considerations

Stefan Bott, Horacio Saggion, Nelson Peréz Rojas +2

Automatic lexical simplification is a task to substitute lexical items that may be unfamiliar and difficult to understand with easier and more common words. This paper presents the…