Optimal path for Biomedical Text Summarization Using Pointer GPT

arXiv:2404.08654v1 Announce Type: new
Abstract: Biomedical text summarization is a critical tool that enables clinicians to effectively ascertain patient status. Traditionally, text summarization has been accomplished with transformer models, which are capable of compressing long documents into brief summaries. However, transformer models are known to be among the most challenging natural language processing (NLP) tasks. Specifically, GPT models have a tendency to generate factual errors, lack context, and oversimplify words. To address these limitations, we replaced the attention mechanism in …

abstract arxiv biomedical clinicians cs.ai cs.cl documents gpt however natural path patient summarization text text summarization tool transformer transformer models type