Console Application Development for Articles` Highlights Generation Based on Artificial Intelligence Designed Using Autonomous Large Language Model

This study explores the development of a console application utilizing autonomous open-source Large Language Models (LLMs), specifically LLAMA 2, to automate the generation of paragraph highlights(outlines) for scientific articles. The research highlights a critical need to enhance the efficiency of processing and reviewing extensive literature, especially in fields overwhelmed with publications such as artificial intelligence. By automating the extraction of key highlights from paragraphs, the application aids researchers in swiftly identifying relevant studies without extensive manual review. Utilizing a qualitative research methodology, the project assesses various LLMs and integrates Whiteside’s method for optimal outlines generation. The findings suggest that the application effectively streamlines the review process, potentially transforming how academic literature is synthesized.