LLM-Guided Planning and Summary-Based Scientific Text Simplification: DS@GT at CLEF 2025 SimpleText
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.
Similar Papers
Hallucination Detection and Mitigation in Scientific Text Simplification using Ensemble Approaches: DS@GT at CLEF 2025 SimpleText
Computation and Language
Checks if simplified science text is true.
SimplifyMyText: An LLM-Based System for Inclusive Plain Language Text Simplification
Computation and Language
Makes hard words easy for everyone to read.
LLM-based Text Simplification and its Effect on User Comprehension and Cognitive Load
Computation and Language
Makes hard web text easy to understand.