SimpCue: Cue-Based Prompting for Multilingual Text Simplification

Abstract:Text simplification aims to make complex texts easier to understand while preserving their original meaning. Recent large language models can perform simplification through prompting, but it remains unclear whether adding explicit linguistic information about sentence complexity to the prompt improves their outputs. We investigate this question for multilingual sentence-level Easy-to-Read simplification in Catalan, Spanish, and Italian. Using Qwen3-8B, we compare a baseline prompt, a gold-cue prompt enriched with gold linguistic cues, and a predicted-cue prompt enriched with automatically predicted cues. We evaluate the outputs using SARI, BLEU, chrF, and BERTScore, and complement this evaluation with a manual qualitative analysis. Predicted-cue prompting obtains the best overall scores across all four metrics, although the gains over the baseline are small. Gold-cue prompting does not consistently improve over the baseline, and results vary across languages. These findings indicate that cue-based prompting can influence multilingual Easy-to-Read simplification, but its benefits are modest, metric-dependent, and language-dependent.

Computation and Language (cs.CL); Artificial Intelligence (cs.AI)

arXiv:2608.28042 [cs.CL]

(or arXiv:2608.28042v1 [cs.CL] for this version)

https://doi.org/10.48550/arXiv.2608.28042 Focus to learn more arXiv-issued DOI via DataCite (pending registration)

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