Search Results - Artificial Intelligence Generated Code Detection

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    AI Generated Code Plagiarism Detection in Computer Science Courses: A Literature Mapping by Simmons, Archer, Holanda, Maristela, Chamon, Christiana, Da Silva, Dilma

    ISSN: 2377-634X
    Published: IEEE 13.10.2024
    “…, methods of plagiarism have evolved, however methods of detection may not be capable of accurately differentiating between code generated by human and artificial intelligence (AI…”
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    Conference Proceeding
  3. 3

    Detecting images generated by diffusers by Coccomini, Davide Alessandro, Esuli, Andrea, Falchi, Fabrizio, Gennaro, Claudio, Amato, Giuseppe

    ISSN: 2376-5992, 2376-5992
    Published: United States PeerJ. Ltd 10.07.2024
    Published in PeerJ. Computer science (10.07.2024)
    “…In recent years, the field of artificial intelligence has witnessed a remarkable surge in the generation of synthetic images, driven by advancements in deep learning techniques…”
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    Journal Article
  4. 4

    Enhancing vulnerability detection by fusing code semantic features with LLM-generated explanations by Tian, Zhenzhou, Li, Minghao, Sun, Jiaze, Chen, Yanping, Chen, Lingwei

    ISSN: 1566-2535
    Published: Elsevier B.V 01.01.2026
    Published in Information fusion (01.01.2026)
    “… This paper proposes FuSEVul, a novel multi-modal framework that integrates code semantics with automatically generated natural language explanations to enhance vulnerability detection…”
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    Journal Article
  5. 5

    A Closer Look at Fourier Spectrum Discrepancies for CNN-generated Images Detection by Chandrasegaran, Keshigeyan, Tran, Ngoc-Trung, Cheung, Ngai-Man

    ISSN: 1063-6919
    Published: IEEE 01.06.2021
    “… Recent works have observed that CNN-generated images share a systematic shortcoming in replicating high frequency Fourier spectrum decay attributes…”
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    Conference Proceeding
  6. 6

    MAGECODE: Machine-Generated Code Detection Method Using Large Language Models by Pham, Hung, Ha, Huyen, Tong, van, Hoang, Dung, Tran, Duc, Le, Tuyen Ngoc

    ISSN: 2169-3536, 2169-3536
    Published: Piscataway IEEE 2024
    Published in IEEE access (2024)
    “… Consequently, various machine-generated text (MGT) detection methods, developed from metric-based and model-based approaches, were proposed and shown to be highly effective…”
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    Journal Article
  7. 7

    Learning on Gradients: Generalized Artifacts Representation for GAN-Generated Images Detection by Tan, Chuangchuang, Zhao, Yao, Wei, Shikui, Gu, Guanghua, Wei, Yunchao

    ISSN: 1063-6919
    Published: IEEE 01.06.2023
    “… In this work, we introduce a novel detection framework, named Learning on Gradients (LGrad), designed for identifying GAN-generated images, with the aim of constructing a generalized detector with cross-model and cross-data…”
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    Conference Proceeding
  8. 8

    Exploring the Boundaries Between LLM Code Clone Detection and Code Similarity Assessment on Human and AI-Generated Code by Zhang, Zixian, Saber, Takfarinas

    ISSN: 2504-2289, 2504-2289
    Published: Basel MDPI AG 01.02.2025
    Published in Big data and cognitive computing (01.02.2025)
    “…As Large Language Models (LLMs) continue to advance, their capabilities in code clone detection have garnered significant attention…”
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    Journal Article
  9. 9

    Assessing AI Detectors in Identifying AI-Generated Code: Implications for Education by Pan, Wei Hung, Chok, Ming Jie, Wong, Jonathan Leong Shan, Shin, Yung Xin, Poon, Yeong Shian, Yang, Zhou, Chong, Chun Yong, Lo, David, Lim, Mei Kuan

    ISSN: 2832-7578
    Published: ACM 14.04.2024
    “…Educators are increasingly concerned about the usage of Large Language Models (LLMs) such as ChatGPT in programming education, particularly regarding the potential exploitation of imperfections in Artificial Intelligence Generated Content…”
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    Conference Proceeding
  10. 10

    Self-generated Defocus Blur Detection via Dual Adversarial Discriminators by Zhao, Wenda, Shang, Cai, Lu, Huchuan

    ISSN: 1063-6919
    Published: IEEE 01.06.2021
    “…Although existing fully-supervised defocus blur detection (DBD) models significantly improve performance, training such deep models requires abundant pixel-level manual annotation, which is highly time-consuming and error-prone…”
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    Conference Proceeding
  11. 11

    Deep-Learning-Empowered Detection of Large-Language-Model-Based Generative Content in Educational Tasks by Su, Zhao, Shen, Jun, Zhou, Qingguo, Yong, Binbin

    ISSN: 1939-1382, 2372-0050
    Published: IEEE 2025
    “…The rapid adoption of large language models (LLMs), such as ChatGPT, in education has intensified the need to differentiate artificial intelligence (AI…”
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    Journal Article
  12. 12

    Artifact feature purification for cross-domain detection of AI-generated images by Meng, Zheling, Peng, Bo, Dong, Jing, Tan, Tieniu, Cheng, Haonan

    ISSN: 1077-3142
    Published: Elsevier Inc 01.10.2024
    Published in Computer vision and image understanding (01.10.2024)
    “… Existing generated image detection methods suffer from performance drops when faced with out-of-domain generators and image scenes…”
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    Journal Article
  13. 13

    Representative Forgery Mining for Fake Face Detection by Wang, Chengrui, Deng, Weihong

    ISSN: 1063-6919
    Published: IEEE 01.06.2021
    “…Although vanilla Convolutional Neural Network (CNN) based detectors can achieve satisfactory performance on fake face detection, we observe that the detectors…”
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    Conference Proceeding
  14. 14

    Self-Supervised Learning for Detecting AI-Generated Faces as Anomalies by Zou, Mian, Yu, Baosheng, Zhan, Yibing, Ma, Kede

    ISSN: 2379-190X
    Published: IEEE 06.04.2025
    “…The detection of AI-generated faces is commonly approached as a binary classification task…”
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    Conference Proceeding
  15. 15

    RAMPAGE: a software framework to ensure reproducibility in algorithmically generated domains detection by Pelayo-Benedet, Tomás, Rodríguez, Ricardo J., Gañán, Carlos H.

    ISSN: 0957-4174
    Published: Elsevier Ltd 01.12.2025
    Published in Expert systems with applications (01.12.2025)
    “…•We introduce Rampage, a framework for reproducible algorithmically generated domains detection comparisons…”
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    Journal Article
  16. 16

    ChatGPT Code Detection: Techniques for Uncovering the Source of Code by Oedingen, Marc, Engelhardt, Raphael C., Denz, Robin, Hammer, Maximilian, Konen, Wolfgang

    ISSN: 2673-2688, 2673-2688
    Published: Basel MDPI AG 01.09.2024
    Published in AI (Basel) (01.09.2024)
    “…In recent times, large language models (LLMs) have made significant strides in generating computer code, blurring the lines between code created by humans and code produced by artificial intelligence (AI…”
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    Journal Article
  17. 17

    Perception matters: Exploring imperceptible and transferable anti-forensics for GAN-generated fake face imagery detection by Wang, Yongwei, Ding, Xin, Yang, Yixin, Ding, Li, Ward, Rabab, Wang, Z. Jane

    ISSN: 0167-8655, 1872-7344
    Published: Amsterdam Elsevier B.V 01.06.2021
    Published in Pattern recognition letters (01.06.2021)
    “…•Propose more imperceptible and transferable anti-forensics for fake face detection…”
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    Journal Article
  18. 18

    What are the differences between student and ChatGPT-generated pseudocode? Detecting AI-generated pseudocode in high school programming using explainable machine learning by Liu, Zifeng, Xing, Wanli, Jiao, Xinyue, Li, Chenglu, Zhu, Wangda

    ISSN: 1360-2357, 1573-7608
    Published: New York Springer US 01.07.2025
    Published in Education and information technologies (01.07.2025)
    “…The ability of large language models (LLMs) to generate code has raised concerns in computer science education, as students may use tools like ChatGPT for programming assignments…”
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    Journal Article
  19. 19

    Hierarchical Fine-Grained Image Forgery Detection and Localization by Guo, Xiao, Liu, Xiaohong, Ren, Zhiyuan, Grosz, Steven, Masi, Iacopo, Liu, Xiaoming

    ISSN: 1063-6919
    Published: IEEE 01.06.2023
    “…Differences in forgery attributes of images generated in CNN-synthesized and image-editing domains are large, and such differences make a unified image forgery detection and localization (IFDL) challenging…”
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    Conference Proceeding
  20. 20

    The imitation game: Detecting human and AI-generated texts in the era of ChatGPT and BARD by Hayawi, Kadhim, Shahriar, Sakib, Mathew, Sujith Samuel

    ISSN: 0165-5515, 1741-6485
    Published: 14.02.2024
    Published in Journal of information science (14.02.2024)
    “…The potential of artificial intelligence (AI)-based large language models (LLMs) holds considerable promise in revolutionising education, research and practice…”
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    Journal Article