The Prompt Report: A Systematic Survey of Prompt Engineering Techniques
Abstrak
Generative Artificial Intelligence (GenAI) systems are increasingly being deployed across diverse industries and research domains. Developers and end-users interact with these systems through the use of prompting and prompt engineering. Although prompt engineering is a widely adopted and extensively researched area, it suffers from conflicting terminology and a fragmented ontological understanding of what constitutes an effective prompt due to its relatively recent emergence. We establish a structured understanding of prompt engineering by assembling a taxonomy of prompting techniques and analyzing their applications. We present a detailed vocabulary of 33 vocabulary terms, a taxonomy of 58 LLM prompting techniques, and 40 techniques for other modalities. Additionally, we provide best practices and guidelines for prompt engineering, including advice for prompting state-of-the-art (SOTA) LLMs such as ChatGPT. We further present a meta-analysis of the entire literature on natural language prefix-prompting. As a culmination of these efforts, this paper presents the most comprehensive survey on prompt engineering to date.
Penulis (31)
Sander Schulhoff
Michael Ilie
Nishant Balepur
Konstantine Kahadze
Amanda Liu
Chenglei Si
Yinheng Li
Aayush Gupta
HyoJung Han
Sevien Schulhoff
Pranav Sandeep Dulepet
Saurav Vidyadhara
Dayeon Ki
Sweta Agrawal
Chau Pham
Gerson Kroiz
Feileen Li
Hudson Tao
Ashay Srivastava
Hevander Da Costa
Saloni Gupta
Megan L. Rogers
Inna Goncearenco
Giuseppe Sarli
Igor Galynker
Denis Peskoff
Marine Carpuat
Jules White
Shyamal Anadkat
Alexander Hoyle
Philip Resnik
Akses Cepat
- Tahun Terbit
- 2024
- Bahasa
- en
- Sumber Database
- arXiv
- Akses
- Open Access ✓