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相关论文: Towards Detecting Prompt Knowledge Gaps for Improv…

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Providing effective feedback is important for student learning in programming problem-solving. In this sense, Large Language Models (LLMs) have emerged as potential tools to automate feedback generation. However, their reliability and…

软件工程 · 计算机科学 2025-03-20 Priscylla Silva , Evandro Costa

Large language models (LLMs) have demonstrated remarkable capabilities in natural language understanding, reasoning, and problem-solving across various domains. However, their ability to perform complex, multi-step reasoning task-essential…

The application of Large Language Models (LLMs) is growing in the productive completion of Software Engineering tasks. Yet, studies investigating the productive prompting techniques often employed a limited problem space, primarily focusing…

软件工程 · 计算机科学 2025-08-07 Sangwon Hyun , Hyunjun Kim , Jinhyuk Jang , Hyojin Choi , M. Ali Babar

Existing knowledge-grounded dialogue systems typically use finetuned versions of a pretrained language model (LM) and large-scale knowledge bases. These models typically fail to generalize on topics outside of the knowledge base, and…

计算与语言 · 计算机科学 2022-03-17 Zihan Liu , Mostofa Patwary , Ryan Prenger , Shrimai Prabhumoye , Wei Ping , Mohammad Shoeybi , Bryan Catanzaro

The use of large language model (LLM)-powered chatbots, such as ChatGPT, has become popular across various domains, supporting a range of tasks and processes. However, due to the intrinsic complexity of LLMs, effective prompting is more…

The dream of achieving a student-teacher ratio of 1:1 is closer than ever thanks to the emergence of large language models (LLMs). One potential application of these models in the educational field would be to provide feedback to students…

计算机与社会 · 计算机科学 2025-05-06 Marc Ballestero-Ribó , Daniel Ortiz-Martínez

This paper introduces DevGPT, a dataset curated to explore how software developers interact with ChatGPT, a prominent large language model (LLM). The dataset encompasses 29,778 prompts and responses from ChatGPT, including 19,106 code…

软件工程 · 计算机科学 2024-02-15 Tao Xiao , Christoph Treude , Hideaki Hata , Kenichi Matsumoto

Large-scale language models (LLMs) have emerged as a groundbreaking innovation in the realm of question-answering and conversational agents. These models, leveraging different deep learning architectures such as Transformers, are trained on…

软件工程 · 计算机科学 2023-07-18 Fardin Ahsan Sakib , Saadat Hasan Khan , A. H. M. Rezaul Karim

Making errors is part of the programming process -- even for the most seasoned professionals. Novices in particular are bound to make many errors while learning. It is well known that traditional (compiler/interpreter) programming error…

软件工程 · 计算机科学 2025-01-13 Audrey Salmon , Katie Hammer , Eddie Antonio Santos , Brett A. Becker

Background: Bug reports are essential to the software development life cycle. They help developers track and resolve issues, but are often difficult to process due to their complexity, which can delay resolution and affect software quality.…

软件工程 · 计算机科学 2025-04-30 Zhiyuan Chen , Vanessa Nava-Camal , Ahmad Suleiman , Yiming Tang , Daqing Hou , Weiyi Shang

This paper presents prompt design techniques for software engineering, in the form of patterns, to solve common problems when using large language models (LLMs), such as ChatGPT to automate common software engineering activities, such as…

软件工程 · 计算机科学 2023-03-15 Jules White , Sam Hays , Quchen Fu , Jesse Spencer-Smith , Douglas C. Schmidt

Programming assistants powered by large language models (LLMs) have become widely available, with conversational assistants like ChatGPT particularly accessible to novice programmers. However, varied tool capabilities and inconsistent…

Large language models (LLMs) such as ChatGPT can produce coherent, cohesive, relevant, and fluent answers for various natural language processing (NLP) tasks. Taking document-level machine translation (MT) as a testbed, this paper provides…

计算与语言 · 计算机科学 2023-10-25 Longyue Wang , Chenyang Lyu , Tianbo Ji , Zhirui Zhang , Dian Yu , Shuming Shi , Zhaopeng Tu

Large Language Models (LLMs) have demonstrated promise in medical knowledge assessments, yet their practical utility in real-world clinical decision-making remains underexplored. In this study, we evaluated the performance of three…

计算与语言 · 计算机科学 2025-12-30 Mengdi Chai , Ali R. Zomorrodi

We introduce Directional Stimulus Prompting, a novel framework for guiding black-box large language models (LLMs) toward specific desired outputs. Instead of directly adjusting LLMs, our method employs a small tunable policy model (e.g.,…

计算与语言 · 计算机科学 2023-10-11 Zekun Li , Baolin Peng , Pengcheng He , Michel Galley , Jianfeng Gao , Xifeng Yan

As large language models (LLMs) become more common in educational tools and programming environments, questions arise about how these systems should interact with users. This study investigates how different interaction styles with…

人机交互 · 计算机科学 2025-07-08 Kai Deng

The advent of Large Language Models (LLMs) has introduced a new paradigm in Software Engineering (SE), with generative AI tools like ChatGPT gaining widespread adoption among developers. While ChatGPT's potential has been extensively…

软件工程 · 计算机科学 2026-02-19 Ruiyin Li , Peng Liang , Yifei Wang , Yangxiao Cai , Weisong Sun , Zengyang Li

Prompting techniques have significantly enhanced the capabilities of Large Language Models (LLMs) across various complex tasks, including reasoning, planning, and solving math word problems. However, most research has predominantly focused…

计算与语言 · 计算机科学 2024-05-24 Neisarg Dave , Daniel Kifer , C. Lee Giles , Ankur Mali

Large Language Models (LLMs) are increasingly deployed to resolve real-world GitHub issues. However, despite their potential, the specific failure modes of these models in complex repair tasks remain poorly understood. To characterize how…

软件工程 · 计算机科学 2026-05-13 Yanjie Jiang , Yian Huang , Guancheng Wang , Junjie Chen , Hui Liu , Lionel Briand

GitHub Actions (GA) has become the de facto tool that developers use to automate software workflows, seamlessly building, testing, and deploying code. Yet when GA fails, it disrupts development, causing delays and driving up costs.…