Top Research Papers on Prompt Engineering

This work infuses into the meta-prompt three key components: detailed descriptions, context specification, and a step-by-step reasoning template that exhibits remarkable versatility across diverse language tasks.

Seit Ende 2022 haben ChatGPT und Co. mehrere Millionen Nutzer*innen gewinnen können – zu diesem Zeitpunkt bekam die breite Masse Zugang zu künstlicher Intelligenz, vor allem aber zu generativer KI. Expert*innen erklärten sich den Hype um die App vor allem durch die einfache Nutzbarkeit: Auch ohne Computer-Kenntnisse zu besitzen, konnten Laien nun einfach mit KI interagieren. Für eine effiziente Nutzung ist es jedoch notwendig, die richtige Handhabung für die Verwendung der großen Sprachmodelle zu finden.

In the context of biomedical engineering, prompt engineering can be used to generate new ideas for research, design new medical devices, and improve the accuracy of clinical diagnoses.

This pictorial presents an ongoing research programme comprising three practice-based Design Research projects conducted through 2024, exploring the affordances of diffusion-based AI image generation systems, specifically Stable Diffusion. The research employs tangible and embodied interactions to investigate emerging qualitative aspects of generative AI, including uncertainty and materiality. Our approach leverages the flexibility and adaptability of Design Research to navigate the rapidly evolving field of generative AI. The pictorial proposes the notion of prompt craft as a productive refra...

Various applications of generative AI prompt engineering in primary care are explored, including enhancing patient–provider communication, streamlining clinical documentation, supporting medical education, and facilitating personalized care and shared decision-making.

Purpose In terms of training the public in prompt engineering skills, no single discipline or profession currently takes the lead, presenting an opportunity for professions like librarianship to step into this role. Librarians are already well-equipped to educate the public in a wide range of literacy skills and tasks, so prompt engineering may be a natural progression. The purpose of this paper is to examine the potential role of prompt engineering for library professionals. Design/methodology/approach Prompt engineering is the process of optimizing the text that is provided to an artifici...

Conversational Prompt Engineering is proposed, a user-friendly tool that helps users create personalized prompts for their specific tasks, using a chat model to briefly interact with users, helping them articulate their output preferences and integrating these into the prompt.

This paper explores a new black-box, zero-shot language model inversion problem and proposes an innovative framework for prompt reconstruction using only text outputs from a language model. Leveraging a large language model alongside an optimization algorithm, the proposed method effectively recovers prompts with minimal resources. Experimental results on several datasets derived from public sources indicate that the proposed approach achieves high-quality prompt recovery and generates prompts more similar to the originals than current state-of-the-art methods. Additionally, the use-case study...

This paper examines Prompt Engineering and evaluates whether it qualifies as a distinct profession, through an analysis of its defining characteristics, including specialized skills, ethical considerations, and societal impact.

It is contended that prompt patterns play an essential role in providing the foundation for prompt engineering, which is a more disciplined and repeatable means of interacting with and evaluating LLMs.

A catalog of prompt engineering techniques presented in pattern form that have been applied to solve common problems when conversing with LLMs to improve the outputs of LLM conversations is described.

A new methodology inspired by codebook construction through qualitative methods is presented that lays a foundation for more systematic, objective, and trustworthy way of applying LLMs for analyzing data.

It is demonstrated that a simple greedy approach with beam search outperforms other methods in terms of search efficiency and two novel techniques that utilize search history to enhance the effectiveness of LLM-based mutation in the authors' search algorithm are introduced.

The study categorizes prompt engineering techniques into instruction-based, information-based, reformulation, and metaphorical prompts, and addresses ethical considerations in prompt engineering, emphasizing the need to mitigate bias and discrimination while ensuring transparency.

The role of “prompt engineers” as a professional title is explored, extending beyond the field of generative AI for developers, comparing certain tasks to the role of librarians, such as conducting search queries.

Artificial intelligence-powered generative language models (GLMs), such as ChatGPT, Perplexity AI, and Google Bard, have the potential to provide personalized learning, unlimited practice opportunities, and interactive engagement 24/7, with immediate feedback. However, to fully utilize GLMs, properly formulated instructions are essential. Prompt engineering is a systematic approach to effectively communicating with GLMs to achieve the desired results. Well-crafted prompts yield good responses from the GLM, while poorly constructed prompts will lead to unsatisfactory responses. Besides the chal...

This paper proposes applying model-driven engineering to support the prompt engineering process using a domain-specific language (DSL), and defines platform-independent prompts that can later be adapted to provide good quality outputs in a target AI system.

By mastering prompt engineering, educators can leverage AI tools as powerful aids, potentially significantly enhancing teaching effectiveness, work efficiency, and student learning outcomes.

A range of recent prompt engineering techniques for GPT-based Codenames agents are compared and qualitative changes in agents’ strategies are observed suggesting that further refinement has potential for score improvement.

With the right approach, nurses can use AI to benefit the profession and patient care.

This study presents Prompt-Eng, a novel framework emphasizing its wide-ranging applications in healthcare, where precise prompts with positive and negative aspects are designed, and it is hypothesize that designing prompts in pairs helps models to generalize effectively.

This playful method provides a new approach to teaching artificial intelligence technologies in higher engineering education, promoting student interaction and engagement.

The purpose of this paper is to study the topic of prompt engineering, which serves as a valuable tool for teachers in creating optimal prompts that effectively enhance students' learning experiences with ChatGPT. This paper explores a variety of strategies related to prompt engineering. These strategies include assigning specific roles to ChatGPT, clearly defining objectives, applying constraints, utilizing structural prompt formats, refining answers through dialogues, and integrating practice exercises. Moreover, this paper specifically delves into relevant approaches to prompt engineering i...

To harness the full potential of LLMs in such crucial contexts, there needs to be a systematic, disciplined approach to "prompt engineering" that guides interactions with and evaluations of these LLMs.

This paper evaluates the effectiveness of the 5 prompt patterns' ability to make GPT-3.5 turbo perform the selected RE tasks and offers recommendations on which prompt pattern to use for a specific RE task and provides an evaluation framework as a reference for researchers and practitioners who want to evaluate different prompt patterns for different RE tasks.

It is found that participants could evaluate prompt quality and crafted descriptive prompts, but they lacked style-specific vocabulary necessary for effective prompting, in line with the hypothesis that prompt engineering is a new type of skill that is non-intuitive and must first be acquired before it can be used.

The development of prompt engineering will be provided and its significant contributions to healthcare natural language processing applications such as question-answering systems, text summarization, and machine translation will be emphasized.

ControlPE enables finer adjustments to prompt effects, complementing existing prompt engineering, and effectively controls continuous targets, proving to be a promising solution for control a variety of prompts.

The development of generative AIs and the variability of their use are still at the level of research and active development simultaneously. However, it has already become clear that the emergence of generative AI significantly impacts many industries, in

It is hypothesized that the way in which users iterate on their prompts can provide insight into how they think prompting and models work, as well as the kinds of support needed for more efficient prompt engineering.

A systematic overview of the privacy protection methods employed during ICL and prompting in general is provided and a detailed examination of the promising areas that necessitate further exploration is offered.

The principles of prompt engineering, applied properly, are demonstrated to be effective in teaching across the diverse fields of anatomy, physiology, pathology, pharmacology, and clinical skills.

This task hopes to spark conversation around the role of computational creativity research in the new world of generative deep learning, and vice versa.

Techniques for measuring the effect that specific words and phrases in prompts have, and guidance on the selection of prompts to produce desired effects are presented.

The utility model provides an engine oil change prompt device, comprising at least one engine oil index detector, a controller and a prompt device that more accurately judges the quality of the engine oil according to the detected engine oil and timely informs the driver.

The idea that many librarians already have the knowledge, skills, abilities and aptitude to do PE is introduced to challenge librarians to consider how it relates to the work that they are doing and consider if it might enhance their current ability to serve users.

The process of prompt engineering to extract link predictions from an LLM is explored, providing detailed insights into the approach for constructing effective prompts, and multiple strategies for leveraging LLMs to generate traceability links are proposed.

This article offers a linguistic perspective on the study of the interaction between humans and Artificial Intelligence. The focus of the work is on analyzing human communication with neural networks which generate textual content. With the advent of text-based interfaces for neural networks, where programming skills are no longer required for human-AI communication, and it is sufficient to create text queries (prompts), one of the key skills for prompt engineers (specialists in prompt creation) has become the ability to ‘program’ and obtain AI responses corresponding to the query while using ...

The results show that reasonable prompt templates can effectively improve the efficiency of automatic vulnerability repair, which is significantly improved compared with neural machine translation technology.

A catalog of prompt engineering techniques, presented in pattern form, that have been applied to solve common problems when conversing with LLMs to aid software development tasks are described.

A new approach to code generation by LLMs is proposed, which is called AlphaCodium - a test-based, multi-stage, code-oriented iterative flow, that improves the performances of LLMs on code problems.

A pioneering taxonomy offers a foundational framework that clarifies the roles of prompt engineering and measures its impact, thereby guiding evolving AI -driven software engineering research and practices.

The research assesses the capabilities of Artificial Intelligence of creating sophisticated and targeted social engineering attacks to exploit human vulnerabilities and revealed some intriguing insights into the efficacy of Artificial Intelligence-generated phishing emails compared to those composed by humans.

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The article is dedicated to the pressing issue of enhancing the effectiveness and quality of training for military prosecutors, investigators, and military police personnel. As a promising solution, the author proposes the use of prompt engineering ― an innovative approach in education based on the application of prompts. The author reveals the potential of prompt engineering in the context of professional training for military lawyers, describes the advantages of personalized learning using prompts, and offers specific methodological approaches based on prompt engineering. The article analyze...

A prompt-based method that uses the existing conversation thread to create natural language prompts for few-shot learning with minimal reliance on training samples is introduced, whose preliminary results suggest that prompt engineering may be a competitive alternative to supervised methods both in terms of accuracy and development costs for the task at hand.

A prototype tool with prompt engineering to fully utilize the educational potential of LLMs and reduce usage for academic dishonesty is developed and will enhance the STEP education by AI.

This short paper identifies five types of prompt modifiers used by practitioners in the community of text-based generative art based on a 3-month ethnographic study on Twitter.

Core concepts, advanced techniques like Chain-of-Thought and Reflection, and the principles behind building LLM-based agents are introduced and a survey of tools for prompt engineers is provided.

This pioneering research introduces the Automatic Prompt Engineering Toolbox (APET), which enables GPT-4 to autonomously apply prompt engineering techniques, resulting in substantial improvements in tasks like Word Sorting and Geometric Shapes.