Natural Language Processing Methods for Abstracting of Scientific Texts

This paper explores the transformative role of Artificial Intelligence (AI) in various sectors, highlighting its growing integration into daily life and consequent ethical and technological implications. Specifically, it examines the potential of Natural Language Processing (NLP)-based AI in generating abstracts for scientific articles, a domain yet to be extensively explored compared to other fields such as healthcare and marketing. By conducting a comprehensive literature review, delving into the principles of AI, and identifying challenges encountered in current research, this study aims to explore the impact of proper prompt engineering on potential generative models’ performance, accuracy and relevance for creating abstracts of scientific articles. The paper also outlines the history of AI, its development in conjunction with NLP, and analyzes best practices to formulate prompts for chatbots, setting the stage for future explorations into the use of AI for academic and scientific purposes.