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相关论文: Prompt Sapper: LLM-Empowered Software Engineering …

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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

This Monte Carlo simulation examines how prompt engineering strategies shape the quality of large language model (LLM)--generated personality assessment items within the AI-GENIE framework for generative psychometrics. Item pools targeting…

人工智能 · 计算机科学 2026-03-18 Lara Lee Russell-Lasalandra , Hudson Golino

With their remarkable ability to generate code, large language models (LLMs) are a transformative technology for computing education practice. They have created an urgent need for educators to rethink pedagogical approaches and teaching…

Artificial Intelligence and especially Large Language Models (LLM), such as ChatGPT has revolutionized the way educators work. The results we get from LLMs depend on how we ask them to help us. The process and the technique behind an…

物理教育 · 物理学 2025-10-13 Dimitrios Gousopoulos

Generative Large Language Models (LLMs) hold significant promise in healthcare, demonstrating capabilities such as passing medical licensing exams and providing clinical knowledge. However, their current use as information retrieval tools…

Large Language Models (LLMs) have the potential to revolutionize automated traceability by overcoming the challenges faced by previous methods and introducing new possibilities. However, the optimal utilization of LLMs for automated…

软件工程 · 计算机科学 2023-08-02 Alberto D. Rodriguez , Katherine R. Dearstyne , Jane Cleland-Huang

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

Over the last decade, a wide range of training and deployment strategies for Large Language Models (LLMs) have emerged. Among these, the prompting paradigms of Auto-regressive LLMs (AR-LLMs) have catalyzed a significant surge in Artificial…

计算与语言 · 计算机科学 2024-05-20 Xinzhe Li , Ming Liu

Recent breakthroughs in Large Language Models (LLMs), such as GPT-3 and Codex, now enable software developers to generate code based on a natural language prompt. Within computer science education, researchers are exploring the potential…

计算机与社会 · 计算机科学 2022-12-13 Stephen MacNeil , Andrew Tran , Juho Leinonen , Paul Denny , Joanne Kim , Arto Hellas , Seth Bernstein , Sami Sarsa

Generative AI is reshaping how software is designed, written, and maintained. Advances in large language models (LLMs) are enabling new development styles - from chat-oriented programming and 'vibe coding' to agentic programming - that can…

软件工程 · 计算机科学 2025-10-14 Vivek Acharya

Large language models have gained widespread prominence, yet their vulnerability to prompt injection and other adversarial attacks remains a critical concern. This paper argues for a security-by-design AI paradigm that proactively mitigates…

密码学与安全 · 计算机科学 2025-10-02 Dalal Alharthi , Ivan Roberto Kawaminami Garcia

To help users do complex work, researchers have developed techniques to integrate AI and human intelligence into user interfaces (UIs). With the recent introduction of large language models (LLMs), which can generate text in response to a…

人机交互 · 计算机科学 2023-07-04 Stephen MacNeil , Andrew Tran , Joanne Kim , Ziheng Huang , Seth Bernstein , Dan Mogil

Upon its release in late 2022, ChatGPT has brought a seismic shift in the entire landscape of AI, both in research and commerce. Through instruction-tuning a large language model (LLM) with supervised fine-tuning and reinforcement learning…

计算与语言 · 计算机科学 2024-01-17 Hailin Chen , Fangkai Jiao , Xingxuan Li , Chengwei Qin , Mathieu Ravaut , Ruochen Zhao , Caiming Xiong , Shafiq Joty

In this paper, we propose a novel prompting approach aimed at enhancing the ability of Large Language Models (LLMs) to generate accurate Python code. Specifically, we introduce a prompt template designed to improve the quality and…

Background: The rapid advancement of large language models (LLMs) has given rise to AI-native applications, a new paradigm in software engineering that fundamentally redefines how software is designed, developed, and evolved. Despite their…

软件工程 · 计算机科学 2025-09-17 Lingli Cao , Shanshan Li , Ying Fan , Danyang Li , Chenxing Zhong

Artificial intelligence's (AI) progress holds great promise in tackling pressing societal concerns such as health and climate. Large Language Models (LLM) and the derived chatbots, like ChatGPT, have highly improved the natural language…

Large Language Models (LLMs) excel in various tasks, but they rely on carefully crafted prompts that often demand substantial human effort. To automate this process, in this paper, we propose a novel framework for discrete prompt…

计算与语言 · 计算机科学 2025-05-02 Qingyan Guo , Rui Wang , Junliang Guo , Bei Li , Kaitao Song , Xu Tan , Guoqing Liu , Jiang Bian , Yujiu Yang

Since their inception, programming languages have trended towards greater readability and lower barriers for programmers. Following this trend, natural language can be a promising type of programming language that provides great flexibility…

计算与语言 · 计算机科学 2024-05-24 Shuyuan Xu , Zelong Li , Kai Mei , Yongfeng Zhang

Human-like large language models (LLMs), especially the most powerful and popular ones in OpenAI's GPT family, have proven to be very helpful for many natural language processing (NLP) related tasks. Therefore, various attempts have been…

计算与语言 · 计算机科学 2024-09-11 Ridong Han , Chaohao Yang , Tao Peng , Prayag Tiwari , Xiang Wan , Lu Liu , Benyou Wang

Human-like large language models (LLMs), especially the most powerful and popular ones in OpenAI's GPT family, have proven to be very helpful for many natural language processing (NLP) related tasks. Therefore, various attempts have been…

计算与语言 · 计算机科学 2024-09-12 Ridong Han , Chaohao Yang , Tao Peng , Prayag Tiwari , Xiang Wan , Lu Liu , Benyou Wang