mlsanityData to 14 Oct 2026

German4All -- A Dataset and Model for Readability-Controlled Paraphrasing in German

arXiv 2508.17973 ↗First posted 25 Aug 2025cs.CLcited by 2

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Abstract (arXiv)

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

Key facts. Cited by 2 papers in the map (data through 14 Oct 2026). Builds on 16 of its 49 references that are in the map. First posted on arXiv 25 Aug 2025.

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16 of 49 references.

References · 16

  1. 2019BERTScore: Evaluating Text Generation with BERTcited by 5,512
  2. 2019Subjective Assessment of Text Complexity: A Dataset for German Languagecited by 17
  3. 2022Klexikon: A German Dataset for Joint Summarization and Simplificationcited by 15
  4. 2023Language Models for German Text Simplification: Overcoming Parallel Data Scarcity through Style-specific Pre-trainingcited by 15
  5. 2024From Tarzan to Tolkien: Controlling the Language Proficiency Level of LLMs for Content Generationcited by 15
  6. 2023DEPLAIN: A German Parallel Corpus with Intralingual Translations into Plain Language for Sentence and Document Simplificationcited by 14
  7. 2024InfoLossQA: Characterizing and Recovering Information Loss in Text Simplificationcited by 14
  8. 2024Analysing Zero-Shot Readability-Controlled Sentence Simplificationcited by 12
  9. 2023Learning to Paraphrase Sentences to Different Complexity Levelscited by 11
  10. 2022A New Aligned Simple German Corpuscited by 10
  11. 2024LL"aMmlein: Transparent, Compact and Competitive German-Only Language Models from Scratchcited by 9
  12. 2025Alignment Drift in CEFR-prompted LLMs for Interactive Spanish Tutoringcited by 7
4 more
  1. 2024German Text Simplification: Finetuning Large Language Models with Semi-Synthetic Datacited by 4
  2. 2025Evaluation Under Imperfect Benchmarks and Ratings: A Case Study in Text Simplificationcited by 4
  3. 2023Data and Approaches for German Text simplification -- towards an Accessibility-enhanced Communicationcited by 2
  4. 2024Images Speak Volumes: User-Centric Assessment of Image Generation for Accessible Communicationcited by 2

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Citing papers per year: 2026: 2.

2 papers.