Document-Level Text Simplification in Estonian Using Large Language Models

Key points

• Document-level text simplification involves transformations that go beyond sentence-internal edits, addressing discourse coherence, anaphora resolution, and cross-paragraph consistency.1
• This study presents a comprehensive evaluation of five state-of-the-art multilingual large language models (LLMs) for document-level simplification in Estonian.1
• The evaluation framework integrates automatic metrics assessing readability, semantic preservation, and discourse coherence, alongside a structured manual annotation protocol.1
• This work contributes novel document-level coherence metrics, evidence-based prompting strategies, and publicly available resources for reproducibility.1

Sources (1)

• [1]Document-Level Text Simplification in Estonian Using Large Language Models
  arXiv (AI, ML, NLP, CV, robotics, multi-agent) · Oct 7, 04:38 PM

  Despite advances in sentence-level simplification for high-resource languages, document-level simplification in morphologically rich, low-resource languages such as Estonian remains largely unexplored.

  Document-level text simplification involves transformations that go beyond sentence-internal edits, addressing discourse coherence, anaphora resolution, and cross-paragraph consistency.

Extractive summary: sentences quoted from the sources.