Document-Level Text Simplification in Estonian Using Large Language Models
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Computer Science > Computation and Language
arXiv:2610.10378 (cs)
[Submitted on 7 Oct 2026]
Title:Document-Level Text Simplification in Estonian Using Large Language Models
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Abstract:Document-level text simplification involves transformations that go beyond sentence-internal edits, addressing discourse coherence, anaphora resolution, and cross-paragraph consistency. 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. This study presents a comprehensive evaluation of five state-of-the-art multilingual large language models (LLMs) for document-level simplification in Estonian. Three prompting strategies are examined: single-pass generation, pipeline-based modular agents, and guideline-augmented pipelines. The evaluation framework integrates automatic metrics assessing readability, semantic preservation, and discourse coherence, alongside a structured manual annotation protocol. The findings indicate that Gemini-2.0 and LLaMA-3.3 produce outputs with near-native fluency and strong meaning preservation, whereas other models display notable grammatical and semantic limitations. This work contributes novel document-level coherence metrics, evidence-based prompting strategies, and publicly available resources for reproducibility.
| Comments: | 12 pages, 2 figures, 2 tables. Published at LREC 2026 |
| Subjects: | Computation and Language (cs.CL) |
| Cite as: | arXiv:2610.10378 [cs.CL] |
| (or arXiv:2610.10378v1 [cs.CL] for this version) | |
| https://doi.org/10.48550/arXiv.2610.10378
arXiv-issued DOI via DataCite (pending registration)
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| Journal reference: | Proceedings of the Fifteenth Language Resources and Evaluation Conference (LREC 2026), pp. 7225-7235, 2026 |
| Related DOI: | https://doi.org/10.63317/3ndqrcjckj32
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View a PDF of the paper titled Document-Level Text Simplification in Estonian Using Large Language Models, by Meeri-Ly Muru and 1 other authors
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