中文
相关论文

相关论文: When Prompt Engineering Meets Software Engineering…

200 篇论文

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

By conditioning on natural language instructions, large language models (LLMs) have displayed impressive capabilities as general-purpose computers. However, task performance depends significantly on the quality of the prompt used to steer…

机器学习 · 计算机科学 2023-03-13 Yongchao Zhou , Andrei Ioan Muresanu , Ziwen Han , Keiran Paster , Silviu Pitis , Harris Chan , Jimmy Ba

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

Natural language (NL) programming has become more approachable due to the powerful code-generation capability of large language models (LLMs). This shift to using NL to program enhances collaborative programming by reducing communication…

人机交互 · 计算机科学 2024-06-18 Li Feng , Ryan Yen , Yuzhe You , Mingming Fan , Jian Zhao , Zhicong Lu

The springing up of Large Language Models (LLMs) has shifted the community from single-task-orientated natural language processing (NLP) research to a holistic end-to-end multi-task learning paradigm. Along this line of research endeavors…

计算与语言 · 计算机科学 2023-10-31 Yuanfeng Song , Yuanqin He , Xuefang Zhao , Hanlin Gu , Di Jiang , Haijun Yang , Lixin Fan , Qiang Yang

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

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

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

Prompts are how humans communicate with LLMs. Informative prompts are essential for guiding LLMs to produce the desired output. However, prompt engineering is often tedious and time-consuming, requiring significant expertise, limiting its…

计算与语言 · 计算机科学 2024-08-09 Liat Ein-Dor , Orith Toledo-Ronen , Artem Spector , Shai Gretz , Lena Dankin , Alon Halfon , Yoav Katz , Noam Slonim

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

The emergence of foundation models, such as large language models (LLMs) GPT-4 and text-to-image models DALL-E, has opened up numerous possibilities across various domains. People can now use natural language (i.e. prompts) to communicate…

软件工程 · 计算机科学 2023-12-21 Yu Cheng , Jieshan Chen , Qing Huang , Zhenchang Xing , Xiwei Xu , Qinghua Lu

Large Language Models (LLMs) are increasingly integrated into software applications, giving rise to a broad class of prompt-enabled systems, in which prompts serve as the primary 'programming' interface for guiding system behavior. Building…

软件工程 · 计算机科学 2026-01-28 Zhenpeng Chen , Chong Wang , Weisong Sun , Xuanzhe Liu , Jie M. Zhang , Yang Liu

Large language models (LLMs) enable system builders today to create competent NLP systems through prompting, where they only need to describe the task in natural language and provide a few examples. However, in other ways, LLMs are a step…

计算与语言 · 计算机科学 2023-08-24 Vijay Viswanathan , Chenyang Zhao , Amanda Bertsch , Tongshuang Wu , Graham Neubig

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

AI-Integrated programming is emerging as a foundational paradigm for building intelligent systems with large language models (LLMs). Recent approaches such as Meaning Typed Programming (MTP) automate prompt generation by leveraging the…

Prompt Engineering (PE) has emerged as a critical technique for guiding Large Language Models (LLMs) in solving intricate tasks. Its importance is highlighted by its potential to significantly enhance the efficiency and effectiveness of…

机器学习 · 计算机科学 2023-11-06 Yifan Luo , Yiming Tang , Chengfeng Shen , Zhennan Zhou , Bin Dong

Large Language Models are transforming software engineering, yet prompt management in practice remains ad hoc, hindering reliability, reuse, and integration into industrial workflows. We present Prompt-with-Me, a practical solution for…

软件工程 · 计算机科学 2025-09-23 Ziyou Li , Agnia Sergeyuk , Maliheh Izadi

Large Language Models (LLMs) have revolutionized human-AI interaction by enabling intuitive task execution through natural language prompts. Despite their potential, designing effective prompts remains a significant challenge, as small…

软件工程 · 计算机科学 2025-04-08 Yuetian Mao , Junjie He , Chunyang Chen

The rapid evolution of large language models (LLMs) has transformed prompt engineering from a localized craft into a systems-level governance challenge. As models scale and update across generations, prompt behavior becomes sensitive to…

计算与语言 · 计算机科学 2026-02-27 Hyunwoo Kim , Hanau Yi , Jaehee Bae , Yumin Kim

The rapid advancements in large language models (LLMs) have greatly expanded the potential for automated code-related tasks. Two primary methodologies are used in this domain: prompt engineering and fine-tuning. Prompt engineering involves…

软件工程 · 计算机科学 2025-02-21 Jiho Shin , Clark Tang , Tahmineh Mohati , Maleknaz Nayebi , Song Wang , Hadi Hemmati
‹ 上一页 1 2 3 10 下一页 ›