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The field of prompt engineering is becoming an essential phenomenon in artificial intelligence. It is altering how data scientists interact with large language models (LLMs) for analytics applications. This research paper shares empirical…

数字图书馆 · 计算机科学 2026-02-03 Snehasish Paul , Rohit Kumar , Laxman Das

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.…

Large language models (LLMs) have shown remarkable performance on many different Natural Language Processing (NLP) tasks. Prompt engineering plays a key role in adding more to the already existing abilities of LLMs to achieve significant…

计算与语言 · 计算机科学 2024-07-25 Shubham Vatsal , Harsh Dubey

Prompt engineering has emerged as an indispensable technique for extending the capabilities of large language models (LLMs) and vision-language models (VLMs). This approach leverages task-specific instructions, known as prompts, to enhance…

人工智能 · 计算机科学 2025-03-18 Pranab Sahoo , Ayush Kumar Singh , Sriparna Saha , Vinija Jain , Samrat Mondal , Aman Chadha

The rapid emergence of generative AI models like Large Language Models (LLMs) has demonstrated its utility across various activities, including within Requirements Engineering (RE). Ensuring the quality and accuracy of LLM-generated output…

软件工程 · 计算机科学 2025-07-08 Krishna Ronanki , Simon Arvidsson , Johan Axell

Prompt engineering has rapidly emerged as a critical skill for effective interaction with large language models (LLMs). However, the cognitive and neural underpinnings of this expertise remain largely unexplored. This paper presents…

Effective prompt engineering is critical to realizing the promised productivity gains of large language models (LLMs) in knowledge-intensive tasks. Yet, many users struggle to craft prompts that yield high-quality outputs, limiting the…

人机交互 · 计算机科学 2025-10-02 Niklas Gutheil , Valentin Mayer , Leopold Müller , Jörg Rommelt , Niklas Kühl

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,…

计算与语言 · 计算机科学 2024-10-18 Aditi Singh , Abul Ehtesham , Gaurav Kumar Gupta , Nikhil Kumar Chatta , Saket Kumar , Tala Talaei Khoei

This comprehensive review delves into the pivotal role of prompt engineering in unleashing the capabilities of Large Language Models (LLMs). The development of Artificial Intelligence (AI), from its inception in the 1950s to the emergence…

计算与语言 · 计算机科学 2025-06-18 Banghao Chen , Zhaofeng Zhang , Nicolas Langrené , Shengxin Zhu

We are witnessing a novel era of creativity where anyone can create digital content via prompt-based learning (known as prompt engineering). This paper investigates prompt engineering as a novel creative skill for creating AI art with…

人机交互 · 计算机科学 2024-07-08 Jonas Oppenlaender , Rhema Linder , Johanna Silvennoinen

The widespread adoption of large language models (LLMs) such as ChatGPT, Gemini, and DeepSeek has significantly changed how people approach tasks in education, professional work, and creative domains. This paper investigates how the…

人机交互 · 计算机科学 2025-08-29 Rizal Khoirul Anam

Interaction with Large Language Models (LLMs) is primarily carried out via prompting. A prompt is a natural language instruction designed to elicit certain behaviour or output from a model. In theory, natural language prompts enable…

人机交互 · 计算机科学 2024-03-15 Michael Desmond , Michelle Brachman

Prompt engineering is crucial for harnessing the potential of large language models (LLMs), especially in the medical domain where specialized terminology and phrasing is used. However, the efficacy of prompt engineering in the medical…

计算与语言 · 计算机科学 2025-07-22 Jamil Zaghir , Marco Naguib , Mina Bjelogrlic , Aurélie Névéol , Xavier Tannier , Christian Lovis

Prompt engineering is a critical technique in the field of natural language processing that involves designing and optimizing the prompts used to input information into models, aiming to enhance their performance on specific tasks. With the…

Large Language Models (LLMs) have revolutionized the field of Natural Language Processing (NLP) by automating traditional labor-intensive tasks and consequently accelerated the development of computer-aided applications. As researchers…

计算与语言 · 计算机科学 2025-06-24 Summra Saleem , Muhammad Nabeel Asim , Shaista Zulfiqar , Andreas Dengel

Artificial intelligence is reshaping labor markets, yet we lack tools to systematically forecast its effects on employment. This paper introduces a benchmark for evaluating how well large language models (LLMs) can anticipate changes in job…

计算与语言 · 计算机科学 2025-10-28 Sheri Osborn , Rohit Valecha , H. Raghav Rao , Dan Sass , Anthony Rios

Prompt engineering has emerged as an integral technique for extending the strengths and abilities of Large Language Models (LLMs) to gain significant performance gains in various Natural Language Processing (NLP) tasks. This approach, which…

计算与语言 · 计算机科学 2026-02-13 Munazza Zaib , Elaf Alhazmi

Prompt engineering has emerged as a powerful technique for guiding large language models (LLMs) toward desired responses, significantly enhancing their performance across diverse tasks. Beyond their role as static predictors, LLMs…

机器学习 · 计算机科学 2025-03-27 Ryumei Nakada , Wenlong Ji , Tianxi Cai , James Zou , Linjun Zhang

Recently, large language models (LLMs) have been successfully applied to many fields, showing outstanding comprehension and reasoning capabilities. Despite their great potential, LLMs usually require dedicated pre-training and fine-tuning…

网络与互联网体系结构 · 计算机科学 2024-12-31 Hao Zhou , Chengming Hu , Dun Yuan , Ye Yuan , Di Wu , Xi Chen , Hina Tabassum , Xue Liu

The rapid advancement of Generative AI (Gen AI) technologies, particularly tools like ChatGPT, is significantly impacting the labor market by reshaping job roles and skill requirements. This study examines the demand for ChatGPT-related…

计算机与社会 · 计算机科学 2024-12-11 Mahdi Ahmadi , Neda Khosh Kheslat , Adebola Akintomide
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