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This paper presents the results of finetuning large language models (LLMs) for the task of detecting vulnerabilities in source code. We leverage WizardCoder, a recent improvement of the state-of-the-art LLM StarCoder, and adapt it for…

密码学与安全 · 计算机科学 2024-07-30 Alexey Shestov , Rodion Levichev , Ravil Mussabayev , Evgeny Maslov , Anton Cheshkov , Pavel Zadorozhny

This paper introduces Safurai-Csharp, an open-source model designed to specialize in the generation, completion, and debugging of C# code. Safurai-Csharp is built upon the novel CodeLlama 34B model and leverages the EvolInstruct technique,…

计算与语言 · 计算机科学 2023-11-07 Davide Cifarelli , Leonardo Boiardi , Alessandro Puppo , Leon Jovanovic

Large Language Models (LLMs) are advanced Artificial Intelligence (AI) systems that have undergone extensive training using large datasets in order to understand and produce language that closely resembles that of humans. These models have…

软件工程 · 计算机科学 2023-08-10 Alessio Buscemi

The advent of Large Language Models (LLMs) has revolutionized code completion, transforming it into a more intelligent and context-aware feature in modern integrated development environments. These advancements have significantly enhanced…

软件工程 · 计算机科学 2025-02-24 Hang Zhang , Yanxin Shen , Lun Wang , Chuanqi Shi , Shaoshuai Du , Yiyi Tao , Yixian Shen

Large language models (LLMs) have achieved remarkable progress in automatic code generation, yet their ability to produce high-performance code remains limited--a critical requirement in real-world software systems. We argue that current…

Recent advancements in Large Language Models (LLMs) and their utilization in code generation tasks have significantly reshaped the field of software development. Despite the remarkable efficacy of code completion solutions in mainstream…

软件工程 · 计算机科学 2024-06-12 Bohdan Petryshyn , Mantas Lukoševičius

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…

编程语言 · 计算机科学 2022-05-05 Frank F. Xu , Uri Alon , Graham Neubig , Vincent J. Hellendoorn

Code Large Language Models (Code LLMs), such as StarCoder, have demonstrated exceptional performance in code-related tasks. However, most existing models are solely pre-trained on extensive raw code data without instruction fine-tuning. In…

计算与语言 · 计算机科学 2025-05-28 Ziyang Luo , Can Xu , Pu Zhao , Qingfeng Sun , Xiubo Geng , Wenxiang Hu , Chongyang Tao , Jing Ma , Qingwei Lin , Daxin Jiang

Generating accurate code review comments remains a significant challenge due to the inherently diverse and non-unique nature of the task output. Large language models pretrained on both programming and natural language data tend to perform…

软件工程 · 计算机科学 2024-11-18 Md. Asif Haider , Ayesha Binte Mostofa , Sk. Sabit Bin Mosaddek , Anindya Iqbal , Toufique Ahmed

The capabilities of Large Language Models (LLMs) have significantly evolved, extending from natural language processing to complex tasks like code understanding and generation. We expand the scope of LLMs' capabilities to a broader context,…

计算与语言 · 计算机科学 2024-10-11 Chenyang Lyu , Lecheng Yan , Rui Xing , Wenxi Li , Younes Samih , Tianbo Ji , Longyue Wang

The advent of Large Language Models (LLM) has revolutionized the efficiency and speed with which tasks are completed, marking a significant leap in productivity through technological innovation. As these chatbots tackle increasingly complex…

软件工程 · 计算机科学 2024-05-24 Luc Bryan Heitz , Joun Chamas , Christopher Scherb

Binary code summarization, while invaluable for understanding code semantics, is challenging due to its labor-intensive nature. This study delves into the potential of large language models (LLMs) for binary code comprehension. To this end,…

密码学与安全 · 计算机科学 2023-12-18 Xin Jin , Jonathan Larson , Weiwei Yang , Zhiqiang Lin

This paper explores the possibilities of the current generation of Large Language Models for incorporating Machine Learning Operations (MLOps) functionalities into ML training code bases. We evaluate the performance of OpenAI…

Since the release of ChatGPT in November 2022, large language models (LLMs) have seen considerable success, including in the open-source community, with many open-weight models available. However, the requirements to deploy such a service…

性能 · 计算机科学 2025-06-13 Yannis Bendi-Ouis , Dan Dutartre , Xavier Hinaut

Large Language Models for code (code LLMs) have witnessed tremendous progress in recent years. With the rapid development of code LLMs, many popular evaluation benchmarks, such as HumanEval, DS-1000, and MBPP, have emerged to measure the…

软件工程 · 计算机科学 2024-11-15 Linyi Li , Shijie Geng , Zhenwen Li , Yibo He , Hao Yu , Ziyue Hua , Guanghan Ning , Siwei Wang , Tao Xie , Hongxia Yang

Large Language Models (LLMs) offer new potential for automating documentation-to-code traceability, yet their capabilities remain underexplored. We present a comprehensive evaluation of LLMs (Claude 3.5 Sonnet, GPT-4o, and o3-mini) in…

软件工程 · 计算机科学 2025-08-08 Ebube Alor , SayedHassan Khatoonabadi , Emad Shihab

The adoption of Large Language Models (LLMs) for code generation in data science offers substantial potential for enhancing tasks such as data manipulation, statistical analysis, and visualization. However, the effectiveness of these models…

General large language models (LLMs), represented by ChatGPT, have demonstrated significant potential in tasks such as code generation in software engineering. This has led to the development of specialized LLMs for software engineering,…

软件工程 · 计算机科学 2024-01-09 Zibin Zheng , Kaiwen Ning , Yanlin Wang , Jingwen Zhang , Dewu Zheng , Mingxi Ye , Jiachi Chen

Large Language Models for Code (Code LLM) are flourishing. New and powerful models are released on a weekly basis, demonstrating remarkable performance on the code generation task. Various approaches have been proposed to boost the code…

As large language models (LLMs) rapidly advance, evaluating their performance is critical. LLMs are trained on multilingual data, but their reasoning abilities are mainly evaluated using English datasets. Hence, robust evaluation frameworks…

计算与语言 · 计算机科学 2025-03-19 Naome A. Etori , Kevin Lu , Randu Karisa , Arturs Kanepajs
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