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Mutation testing is vital for ensuring software quality. However, the presence of equivalent mutants is known to introduce redundant cost and bias issues, hindering the effectiveness of mutation testing in practical use. Although numerous…

Software Engineering · Computer Science 2024-08-06 Zhao Tian , Honglin Shu , Dong Wang , Xuejie Cao , Yasutaka Kamei , Junjie Chen

In this paper, we propose a feature pioneering method using Large Language Models (LLMs). In the proposed method, we use Chat-GPT 1 to find new sensor locations and new features. Then we evaluate the machine learning model which uses the…

Human-Computer Interaction · Computer Science 2023-10-10 Haru Kaneko , Sozo Inoue

While defenses against single-turn jailbreak attacks on Large Language Models (LLMs) have improved significantly, multi-turn jailbreaks remain a persistent vulnerability, often achieving success rates exceeding 70% against models optimized…

Machine Learning · Computer Science 2025-08-12 Xiaoxue Yang , Jaeha Lee , Anna-Katharina Dick , Jasper Timm , Fei Xie , Diogo Cruz

This paper explores the potential of large language models (LLMs) as reliable analytical tools in linguistic research, focusing on the emergence of affective meanings in temporal expressions involving manner-of-motion verbs. While LLMs like…

Computation and Language · Computer Science 2025-07-15 Rosa Illan Castillo , Javier Valenzuela

The increasing digitization of smart grids has improved operational efficiency but also introduced new cybersecurity vulnerabilities, such as False Data Injection Attacks (FDIAs) targeting Automatic Generation Control (AGC) systems. While…

Cryptography and Security · Computer Science 2025-08-27 Muhammad Sharshar , Ahmad Mohammad Saber , Davor Svetinovic , Amr M. Youssef , Deepa Kundur , Ehab F. El-Saadany

Large Language Models (LLMs) like GPT-4 and Gemini have significantly advanced artificial intelligence by enabling machines to generate and comprehend human-like text. Despite their impressive capabilities, LLMs are not immune to…

Computation and Language · Computer Science 2024-12-19 Jiaxu Lou , Yifan Sun

Large vision-language models (LVLMs) have been regarded as a breakthrough advance in an astoundingly variety of tasks, from content generation to virtual assistants and multimodal search or retrieval. However, for many of these…

Computer Vision and Pattern Recognition · Computer Science 2025-02-03 Kailash Hambarde , Pranita Samale , Hugo Proença

Malicious traffic detection is a pivotal technology for network security to identify abnormal network traffic and detect network attacks. Large Language Models (LLMs) are trained on a vast corpus of text, have amassed remarkable…

Networking and Internet Architecture · Computer Science 2025-06-24 Xinggong Zhang , Haotian Meng , Qingyang Li , Yunpeng Tan , Lei Zhang

Recent advances in biometric systems have significantly improved the detection and prevention of fraudulent activities. However, as detection methods improve, attack techniques become increasingly sophisticated. Attacks on face recognition…

Computer Vision and Pattern Recognition · Computer Science 2025-07-22 Lazaro Janier Gonzalez-Soler , Maciej Salwowski , Christoph Busch

Large Language Models (LLMs) have achieved remarkable success recently, displaying exceptional capabilities in creating understandable and organized text. These LLMs have been utilized in diverse fields, such as clinical research, where…

Statistical Finance · Quantitative Finance 2025-01-17 Shuoling Liu , Gaoguo Jia , Yuhang Jiang , Liyuan Chen , Qiang Yang

Adult neurodivergence, including Attention-Deficit/Hyperactivity Disorder (ADHD), high-functioning Autism Spectrum Disorder (ASD), and Cognitive Disengagement Syndrome (CDS), is marked by substantial symptom overlap that limits the…

Neurons and Cognition · Quantitative Biology 2026-01-23 Francesco Chiappone , Davide Marocco , Nicola Milano

Large Language Models (LLMs) have garnered considerable interest within both academic and industrial. Yet, the application of LLMs to graph data remains under-explored. In this study, we evaluate the capabilities of four LLMs in addressing…

Artificial Intelligence · Computer Science 2023-09-12 Chang Liu , Bo Wu

Test smells are coding issues that typically arise from inadequate practices, a lack of knowledge about effective testing, or deadline pressures to complete projects. The presence of test smells can negatively impact the maintainability and…

Software Engineering · Computer Science 2024-07-31 Keila Lucas , Rohit Gheyi , Elvys Soares , Márcio Ribeiro , Ivan Machado

Large Language Models (LLMs) have revolutionized Artificial Intelligence (AI) services due to their exceptional proficiency in understanding and generating human-like text. LLM chatbots, in particular, have seen widespread adoption,…

Cryptography and Security · Computer Science 2024-02-14 Gelei Deng , Yi Liu , Yuekang Li , Kailong Wang , Ying Zhang , Zefeng Li , Haoyu Wang , Tianwei Zhang , Yang Liu

Large language models (LLMs) have undergone significant expansion and have been increasingly integrated across various domains. Notably, in the realm of robot task planning, LLMs harness their advanced reasoning and language comprehension…

In this study, we investigate the use of large language models (LLMs), specifically ChatGPT, for structured deductive qualitative coding. While most current research emphasizes inductive coding applications, we address the underexplored…

Human-Computer Interaction · Computer Science 2025-07-22 Angjelin Hila , Elliott Hauser

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…

A significant application of Large Language Models (LLMs), like ChatGPT, is their deployment as chat agents, which respond to human inquiries across a variety of domains. While current LLMs proficiently answer general questions, they often…

Computation and Language · Computer Science 2024-04-16 Lang Cao

Diffusion Multi-modal Large Language Models (dMLLMs) have recently emerged as a novel architecture unifying image generation and understanding. However, developing effective and efficient Test-Time Scaling (TTS) methods to unlock their full…

Computer Vision and Pattern Recognition · Computer Science 2026-04-09 Yi Xin , Siqi Luo , Tianxiang Xu , Qi Qin , Haoxing Chen , Kaiwen Zhu , Zhiwei Zhang , Yangfan He , Rongchao Zhang , Jinbin Bai , Shuo Cao , Bin Fu , Junjun He , Yihao Liu , Yuewen Cao , Xiaohong Liu

With the significant development of large models in recent years, Large Vision-Language Models (LVLMs) have demonstrated remarkable capabilities across a wide range of multimodal understanding and reasoning tasks. Compared to traditional…

Computer Vision and Pattern Recognition · Computer Science 2024-07-15 Daizong Liu , Mingyu Yang , Xiaoye Qu , Pan Zhou , Yu Cheng , Wei Hu