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Artem Ryblov’s Data Science Weekly Artem Ryblov’s Data Science Weekly @data_science_weekly · 686 subscribers
Post #181 691
The Prompt Report: A Systematic Survey of Prompt Engineering Techniques

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.

Authors establish a structured understanding of prompt engineering by assembling a taxonomy of prompting techniques and analyzing their applications. They present a detailed vocabulary of 33 vocabulary terms, a taxonomy of 58 LLM prompting techniques, and 40 techniques for other modalities.

Additionally, authors provide best practices and guidelines for prompt engineering, including advice for prompting state-of-the-art (SOTA) LLMs such as ChatGPT. They 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.

Link: ArXiv

Navigational hashtags: #armarticles
General hashtags: #promptengineering #prompts #prompt #llm

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