German4All - A Dataset and Model for Readability-Controlled Paraphrasing
  in German
Authors: name: Miriam Anschütz; name: Thanh Mai Pham; name: Eslam Nasrallah; name: Maximilian Müller; name: Cristian-George Craciun; name: Georg Groh
Published: 2025-08-25 12:40:32

Abstract: The ability to paraphrase texts across different complexity levels is
essential for creating accessible texts that can be tailored toward diverse
reader groups. Thus, we introduce German4All, the first large-scale German
dataset of aligned readability-controlled, paragraph-level paraphrases. It
spans five readability levels and comprises over 25,000 samples. The dataset is
automatically synthesized using GPT-4 and rigorously evaluated through both
human and LLM-based judgments. Using German4All, we train an open-source,
readability-controlled paraphrasing model that achieves state-of-the-art
performance in German text simplification, enabling more nuanced and
reader-specific adaptations. We opensource both the dataset and the model to
encourage further research on multi-level paraphrasing