LLM-Guided Planning and Summary-Based Scientific Text Simplification: DS@GT at CLEF 2025 SimpleText
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Abstract (arXiv)
In this paper, we present our approach for the CLEF 2025 SimpleText Task 1, which addresses both sentence-level and document-level scientific text simplification. For sentence-level simplification, our methodology employs large language models (LLMs) to first generate a structured plan, followed by plan-driven simplification of individual sentences. At the document level, we leverage LLMs to produce concise summaries and subsequently guide the simplification process using these summaries. This two-stage, LLM-based framework enables more coherent and contextually faithful simplifications of scientific text.
Key facts. Cited by 2 papers in the map (data through 14 Oct 2026). Builds on 2 of its 14 references that are in the map. First posted on arXiv 15 Aug 2025.
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2 of 14 references.
References · 2
- 2019BERTScore: Evaluating Text Generation with BERTcited by 5,512
- 2025Progressive Document-level Text Simplification via Large Language Modelscited by 5
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Citing papers per year: 2025: 1; 2026: 1.
2 papers.