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Found 2 papers, 2 papers with code
RAG-RLRC-LaySum at BioLaySumm: Integrating Retrieval-Augmented Generation and Readability Control for Layman Summarization of Biomedical Texts
This paper introduces the RAG-RLRC-LaySum framework, designed to make complex biomedical research understandable to laymen through advanced Natural Language Processing (NLP) techniques.
Assertion Detection Large Language Model In-context Learning LoRA Fine-tuning
To further assess the generalizability of our approach, we extended our evaluation to a local dataset that focused on sleep concept extraction.
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