Shared Task at Biolaysumm2025 : Extract then summarize approach Augmented with UMLS based Definition Retrieval for Lay Summary generation.
Year: 2025
Type: conference-paper
Abstract: We present LayForge, a two-track lay summary generation system developed for the Bio-LaySumm2025 shared task (Xiao et al., 2025) .Task 1.1 addresses the lay summarization using only the internal content of the article, while Task 1.2 augments this process with domain knowledge such as biomedical definitions and concept explanations.BioLaySumm employs a modular architecture that leverages large language models (LLMs), a BioBERTbased named entity recognizer (NER), and the UMLS (Bodenreider, 2004) knowledge base to create readable, informative, and faithful lay summaries.Our system shows strong performance on both tasks when evaluated on the PLOS and elife subset (Goldsack et al., 2022), particularly in readability and factuality metrics.The architecture illustrates how modularity and domain adaptation can be effectively combined for accessible biomedical communication.
Authors: Aaradhya Gupta, Parameswari Krishnamurthy
Language: English
Subfield: Molecular Biology
Domain: Life Sciences
Open Access status: hybrid
OpenAlex ID: W4412889078