German Text Simplification: Finetuning Large Language Models with Semi-Synthetic Data

arXiv:2402.10675v1 Announce Type: new
Abstract: This study pioneers the use of synthetically generated data for training generative models in document-level text simplification of German texts. We demonstrate the effectiveness of our approach with real-world online texts. Addressing the challenge of data scarcity in language simplification, we crawled professionally simplified German texts and synthesized a corpus using GPT-4. We finetune Large Language Models with up to 13 billion parameters on this data and evaluate their performance. This paper employs various methodologies …

abstract arxiv challenge cs.cl data document finetuning generated generative generative models german language language models large language large language models simplified study synthetic synthetic data text training type world