用提示词引入语言特征，提升多语种文本简化效果。
SimpCue: Cue-Based Prompting for Multilingual Text Simplification
- 在提示词中加入句法复杂度线索，引导模型简化文本。
- 自动预测线索的提示比基线提升显著，但增幅有限。
- 效果受评估指标和语言影响，需谨慎应用。
文本简化旨在保持原意的前提下使复杂文本更易理解。近期大语言模型可通过提示词实现简化，但尚不清楚在提示中加入显式的句法复杂度信息是否能提升效果。本文针对加泰罗尼亚语、西班牙语和意大利语的多语种句子级易读性简化任务，使用 Qwen3-8B 模型比较三种提示方式：基线提示、基于人工标注线索的黄金提示（gold-cue prompt）以及基于自动预测线索的提示（predicted-cue prompt）。采用 SARI、BLEU、chrF 与 BERTScore 四项指标进行评估，并辅以人工定性分析。结果表明，预测线索提示在四项指标上整体表现最优，但相较于基线提升微弱；黄金线索提示并未一致优于基线，且不同语言间表现差异明显。研究显示，基于线索的提示对多语种易读性简化有影响，但收益有限，且依赖于评估指标和目标语言。
原文摘要 · Abstract (English)
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.
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