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LLM-Guided Planning and Summary-Based Scientific Text Simplification: DS@GT at CLEF 2025 SimpleText

Published: August 15, 2025 | arXiv ID: 2508.11816v1

By: Krishna Chaitanya Marturi, Heba H. Elwazzan

Potential Business Impact:

Makes science papers easy to understand.

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.

Country of Origin
🇺🇸 United States

Page Count
10 pages

Category
Computer Science:
Computation and Language