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A Systematic Literature Review on SWOT Analysis of Prompt Engineering Techniques

  • Aditi Singh
  • , Nikhil Kumar Chatta
  • , Abul Ehtesham
  • , Saket Kumar
  • , Gaurav Kumar Gupta
  • , Tala Talaei Khoei
  • Cleveland State University
  • Kent State University
  • Northeastern University
  • Youngstown State University
  • Khoury College of Computer Sciences

Research output: Contribution to journalReview articlepeer-review

2 Scopus citations

Abstract

This paper reviews how prompt engineering can optimize interactions with advanced AI systems called Large Language Models (LLMs). Prompt engineering involves designing inputs like questions or instructions that guide AI to produce accurate and useful responses. These techniques are analyzed using a SWOT framework (strengths, weaknesses, opportunities, and threats), offering insights for researchers and developers. Additionally, applications across industries such as healthcare, education, and customer service are discussed, while highlighting challenges such as maintaining accuracy and efficiency. The findings aim to advance human-machine communication in both general and domain-specific contexts.
Original languageEnglish
Number of pages15
JournalIEEE Transactions on Artificial Intelligence
DOIs
StateAccepted/In press - Jan 1 2025

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

Keywords

  • Large Language Model
  • Natural Language Processing
  • Prompt Engineering
  • Prompt Engineering Techniques

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