Summary of The Prompt Report: a Systematic Survey Of Prompt Engineering Techniques, by Sander Schulhoff et al.

The Prompt Report: A Systematic Survey of Prompt Engineering Techniques

by 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

First submitted to arxiv on: 6 Jun 2024

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Summary difficulty	Written by	Summary
High	Paper authors	High Difficulty Summary Read the original abstract here
Medium	GrooveSquid.com (original content)	Medium Difficulty Summary The abstract proposes a systematic understanding of prompt engineering in generative AI systems. The authors develop a taxonomy of 58 LLM prompting techniques and 40 techniques for other modalities, along with a vocabulary of 33 terms. They also provide guidelines for prompt engineering, including advice on prompting state-of-the-art LLMs like ChatGPT. Additionally, the paper presents a meta-analysis of natural language prefix-prompting literature. The authors’ comprehensive survey aims to unify the fragmented understanding of effective prompts in this emerging field.
Low	GrooveSquid.com (original content)	Low Difficulty Summary The abstract is about how people interact with artificial intelligence systems using special instructions called “prompts”. Right now, there’s confusion about what makes a good prompt because different people use different words and ideas. To fix this, the authors created a system to organize and understand all the different ways to give prompts. They also gave advice on how to make the best prompts for special AI models like ChatGPT.