Exploring Prompt Engineering: A Systematic Review with SWOT Analysis

Aditi Singh, Abul Ehtesham, Gaurav Kumar Gupta, Nikhil Kumar Chatta, Saket Kumar +1 more
10/9/2024
cs.CLcs.AI

No confident code implementation found for this paper.

Abstract

In this paper, we conduct a comprehensive SWOT analysis of prompt engineering techniques within the realm of Large Language Models (LLMs). Emphasizing linguistic principles, we examine various techniques to identify their strengths, weaknesses, opportunities, and threats. Our findings provide insights into enhancing AI interactions and improving language model comprehension of human prompts. The analysis covers techniques including template-based approaches and fine-tuning, addressing the problems and challenges associated with each. The conclusion offers future research directions aimed at advancing the effectiveness of prompt engineering in optimizing human-machine communication.

View on arXivView PDF

Code Implementations

No confident code match yet

We couldn't find an author-owned or strongly-evidenced community implementation for this paper. Any repos shown below are weak matches — verify before relying on them.

No code implementations found yet.

Know of an implementation? Let us know in the comments below!

Similar Papers

Towards Goal-oriented Prompt Engineering for Large Language Models: A Survey

88% match1 repo592024

A Systematic Survey of Prompt Engineering in Large Language Models: Techniques and Applications

88% match1 repo2024

Prompt Engineering a Prompt Engineer

88% match1 repo122023

A Survey of Prompt Engineering Methods in Large Language Models for Different NLP Tasks

87% match2024

Prompt Design and Engineering: Introduction and Advanced Methods

86% match2024

Autonomous Prompt Engineering in Large Language Models

86% match2024

Cite this paper

@article{singh2024exploring,
  title  = {Exploring Prompt Engineering: A Systematic Review with SWOT Analysis},
  author = {Aditi Singh and Abul Ehtesham and Gaurav Kumar Gupta and Nikhil Kumar Chatta and Saket Kumar and Tala Talaei Khoei},
  year   = {2024},
  eprint = {2410.12843},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2410.12843v1}
}

Add a badge to your README

Shows whether official code is linked for this paper.

Code of Paper badge
[![Code of Paper](https://codeofpaper.com/badge/2410.12843.svg)](https://codeofpaper.com/paper/2410.12843)

Discussion