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Recently, large language models (LLM) based generative AI has been gaining momentum for their impressive high-quality performances in multiple domains, particularly after the release of the ChatGPT. Many believe that they have the potential…

Software Engineering · Computer Science 2024-02-22 Wei Wang , Huilong Ning , Gaowei Zhang , Libo Liu , Yi Wang

Recently, researchers have proposed many multi-agent frameworks for function-level code generation, which aim to improve software development productivity by automatically generating function-level source code based on task descriptions. A…

Software Engineering · Computer Science 2025-04-08 Yueheng Zhu , Chao Liu , Xuan He , Xiaoxue Ren , Zhongxin Liu , Ruwei Pan , Hongyu Zhang

The rise of large language models (LLMs) like ChatGPT has significantly improved automated code generation, enhancing software development efficiency. However, this introduces challenges in academia, particularly in distinguishing between…

Software Engineering · Computer Science 2025-01-08 Zhenyu Xu , Victor S. Sheng

Large language models (LLMs) have shown great potential in automating significant aspects of coding by producing natural code from informal natural language (NL) intent. However, given NL is informal, it does not lend easily to checking…

Software Engineering · Computer Science 2024-10-04 Sarah Fakhoury , Aaditya Naik , Georgios Sakkas , Saikat Chakraborty , Shuvendu K. Lahiri

The transformative influence of Large Language Models (LLMs) is profoundly reshaping the Artificial Intelligence (AI) technology domain. Notably, ChatGPT distinguishes itself within these models, demonstrating remarkable performance in…

Software Engineering · Computer Science 2024-05-28 Sayed Erfan Arefin , Tasnia Ashrafi Heya , Hasan Al-Qudah , Ynes Ineza , Abdul Serwadda

Large Language Models (LLMs), such as GPT-4, StarCoder, and CodeLlama, are transforming the way developers approach programming by automatically generating code based on given natural language descriptions. Despite advancements, generating…

Software Engineering · Computer Science 2024-09-20 Zhihong Sun , Yao Wan , Jia Li , Hongyu Zhang , Zhi Jin , Ge Li , Chen Lyu

Recent work demonstrates that, after instruction tuning, Code Large Language Models (Code LLMs) can obtain impressive capabilities to address a wide range of code-related tasks. However, current instruction tuning methods for Code LLMs…

Computation and Language · Computer Science 2024-06-10 Zhaojian Yu , Xin Zhang , Ning Shang , Yangyu Huang , Can Xu , Yishujie Zhao , Wenxiang Hu , Qiufeng Yin

Task automation has been greatly empowered by the recent advances in Large Language Models (LLMs) via Python code, where the tasks ranging from software engineering development to general-purpose reasoning. While current benchmarks have…

Code translation is a crucial activity in the software development and maintenance process, and researchers have recently begun to focus on using pre-trained large language models (LLMs) for code translation. However, existing LLMs only…

Software Engineering · Computer Science 2025-09-30 Minghua He , Yue Chen , Fangkai Yang , Pu Zhao , Wenjie Yin , Yu Kang , Qingwei Lin , Saravan Rajmohan , Dongmei Zhang

The recently released GPT-4 Code Interpreter has demonstrated remarkable proficiency in solving challenging math problems, primarily attributed to its ability to seamlessly reason with natural language, generate code, execute code, and…

Computation and Language · Computer Science 2023-10-06 Ke Wang , Houxing Ren , Aojun Zhou , Zimu Lu , Sichun Luo , Weikang Shi , Renrui Zhang , Linqi Song , Mingjie Zhan , Hongsheng Li

This paper investigates how large language models (LLMs) behave when faced with discrepancies between their parametric knowledge and conflicting information contained in a prompt. Building on prior question-answering (QA) research, we…

Computation and Language · Computer Science 2025-10-23 Jaesung Bae , Cameron Churchwell , Mitchell Hermon , Tsun-An Hsieh , Jocelyn Xu , Yekaterina Yegorova , Mark Hasegawa-Johnson , Heng Ji

Large Language Models (LLMs) have recently been widely used for code generation. Due to the complexity and opacity of LLMs, little is known about how these models generate code. We made the first attempt to bridge this knowledge gap by…

Software Engineering · Computer Science 2024-05-24 Bonan Kou , Shengmai Chen , Zhijie Wang , Lei Ma , Tianyi Zhang

Recently, the large language models (LLMs) have shown extraordinary ability in understanding natural language and generating programming code. It has been a common practice of software engineers to consult LLMs when encountering coding…

Computation and Language · Computer Science 2024-01-30 Li Zhong , Zilong Wang

Despite many advances in knowledge engineering (KE), challenges remain in areas such as engineering knowledge graphs (KGs) at scale, keeping up with evolving domain knowledge, multilingualism, and multimodality. Recently, KE has used LLMs…

Human-Computer Interaction · Computer Science 2025-10-23 Elisavet Koutsiana , Johanna Walker , Michelle Nwachukwu , Bohui Zhang , Albert Meroño-Peñuela , Elena Simperl

Large language models (LLMs) have led to a series of breakthroughs in natural language processing (NLP), owing to their excellent understanding and generation abilities. Remarkably, what further sets these models apart is the massive…

Computation and Language · Computer Science 2022-11-10 Daliang Li , Ankit Singh Rawat , Manzil Zaheer , Xin Wang , Michal Lukasik , Andreas Veit , Felix Yu , Sanjiv Kumar

Large language models (LMs) of code have recently shown tremendous promise in completing code and synthesizing code from natural language descriptions. However, the current state-of-the-art code LMs (e.g., Codex (Chen et al., 2021)) are not…

Programming Languages · Computer Science 2022-05-05 Frank F. Xu , Uri Alon , Graham Neubig , Vincent J. Hellendoorn

The development of large language models (LLMs) has revolutionized automated code generation. However, their high demand of computation resources has hindered a broader deployment and raised environmental concerns. A common strategy for…

Software Engineering · Computer Science 2024-11-12 Xiangyu Zhang , Yu Zhou , Guang Yang , Harald C. Gall , Taolue Chen

Large Language Models (LLMs) are becoming integral to modern software development workflows, assisting developers with code generation, API explanation, and iterative problem-solving through natural language conversations. Despite…

Software Engineering · Computer Science 2025-09-15 Suzhen Zhong , Ying Zou , Bram Adams

Large language models (LLMs) have become increasingly prominent in academia and industry due to their remarkable performance in diverse applications. As these models evolve with increasing parameters, they excel in tasks like sentiment…

Machine Learning · Computer Science 2023-11-14 Le Chen , Arijit Bhattacharjee , Nesreen K. Ahmed , Niranjan Hasabnis , Gal Oren , Bin Lei , Ali Jannesari

Code generation with Large Language Models (LLMs) has been extensively studied and achieved remarkable progress. As a complementary aspect to code generation, test case generation is of crucial importance in ensuring the quality and…

Software Engineering · Computer Science 2024-04-23 Kefan Li , Yuan Yuan