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

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