{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,3]],"date-time":"2026-06-03T00:49:39Z","timestamp":1780447779911,"version":"3.54.1"},"publisher-location":"Cham","reference-count":35,"publisher":"Springer Nature Switzerland","isbn-type":[{"value":"9783032060778","type":"print"},{"value":"9783032060785","type":"electronic"}],"license":[{"start":{"date-parts":[[2025,9,30]],"date-time":"2025-09-30T00:00:00Z","timestamp":1759190400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2025,9,30]],"date-time":"2025-09-30T00:00:00Z","timestamp":1759190400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2026]]},"DOI":"10.1007\/978-3-032-06078-5_11","type":"book-chapter","created":{"date-parts":[[2025,9,29]],"date-time":"2025-09-29T18:50:17Z","timestamp":1759171817000},"page":"187-204","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Zero-Shot Detection of\u00a0LLM-Generated Code via\u00a0Approximated Task Conditioning"],"prefix":"10.1007","author":[{"given":"Maor","family":"Ashkenazi","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ofir","family":"Brenner","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Tal Furman","family":"Shohet","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Eran","family":"Treister","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2025,9,30]]},"reference":[{"key":"11_CR1","unstructured":"Anthropic (2024). https:\/\/www.anthropic.com\/"},{"key":"11_CR2","unstructured":"OpenAI (2024). https:\/\/openai.com\/api"},{"key":"11_CR3","unstructured":"Stack overflow developer survey (2024). https:\/\/survey.stackoverflow.co\/2024\/"},{"key":"11_CR4","unstructured":"Meta AI, llama 3.1 (2024). https:\/\/llama.meta.com\/"},{"key":"11_CR5","unstructured":"Austin, J., et\u00a0al.: Program synthesis with large language models. arXiv preprint arXiv:2108.07732 (2021)"},{"key":"11_CR6","unstructured":"Bakhtin, A., Gross, S., Ott, M., Deng, Y., Ranzato, M., Szlam, A.: Real or fake? Learning to discriminate machine from human generated text. arXiv preprint arXiv:1906.03351 (2019)"},{"key":"11_CR7","unstructured":"Bao, G., Zhao, Y., Teng, Z., Yang, L., Zhang, Y.: Fast-DetectGPT: efficient zero-shot detection of machine-generated text via conditional probability curvature. arXiv preprint arXiv:2310.05130 (2023)"},{"key":"11_CR8","unstructured":"Bommasani, R., et\u00a0al.: On the opportunities and risks of foundation models. arXiv preprint arXiv:2108.07258 (2021)"},{"key":"11_CR9","doi-asserted-by":"crossref","unstructured":"Demirok, B., Kutlu, M.: AIGCodeSet: a new annotated dataset for AI generated code detection. arXiv preprint arXiv:2412.16594 (2024)","DOI":"10.1109\/SIU66497.2025.11112334"},{"key":"11_CR10","doi-asserted-by":"crossref","unstructured":"Gehrmann, S., Strobelt, H., Rush, A.: GLTR: statistical detection and visualization of generated text. In: Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics: System Demonstrations. Association for Computational Linguistics (2019)","DOI":"10.18653\/v1\/P19-3019"},{"key":"11_CR11","unstructured":"Hendrycks, D., et al.: Measuring coding challenge competence with APPS. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021)"},{"key":"11_CR12","unstructured":"Huang, X.Y., Vishnubhotla, K., Rudzicz, F.: The GPT-WritingPrompts Dataset: a comparative analysis of character portrayal in short stories. arXiv preprint arXiv:2406.16767 (2024)"},{"key":"11_CR13","doi-asserted-by":"crossref","unstructured":"Jawahar, G., Abdul-Mageed, M., Laks\u00a0Lakshmanan, V.: Automatic detection of machine generated text: a critical survey. In: Proceedings of the 28th International Conference on Computational Linguistics, pp. 2296\u20132309 (2020)","DOI":"10.18653\/v1\/2020.coling-main.208"},{"key":"11_CR14","doi-asserted-by":"crossref","unstructured":"Lee, T., et al.: Who wrote this code? watermarking for code generation. In: Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), pp. 4890\u20134911 (2024)","DOI":"10.18653\/v1\/2024.acl-long.268"},{"issue":"6624","key":"11_CR15","doi-asserted-by":"publisher","first-page":"1092","DOI":"10.1126\/science.abq1158","volume":"378","author":"Y Li","year":"2022","unstructured":"Li, Y., et al.: Competition-level code generation with AlphaCode. Science 378(6624), 1092\u20131097 (2022)","journal-title":"Science"},{"key":"11_CR16","unstructured":"Mitchell, E., Lee, Y., Khazatsky, A., Manning, C.D., Finn, C.: DetectGPT: zero-shot machine-generated text detection using probability curvature. In: International Conference on Machine Learning, pp. 24950\u201324962. PMLR (2023)"},{"key":"11_CR17","unstructured":"Mitrovi\u0107, S., Andreoletti, D., Ayoub, O.: ChatGPT or Human? Detect and explain. explaining decisions of machine learning model for detecting short ChatGPT-generated text. arXiv preprint arXiv:2301.13852 (2023)"},{"key":"11_CR18","doi-asserted-by":"crossref","unstructured":"Pu, J., et al.: Deepfake text detection: limitations and opportunities. In: 2023 IEEE Symposium on Security and Privacy (SP), pp. 1613\u20131630 (2023)","DOI":"10.1109\/SP46215.2023.10179387"},{"issue":"140","key":"11_CR19","first-page":"1","volume":"21","author":"C Raffel","year":"2020","unstructured":"Raffel, C., et al.: Exploring the limits of transfer learning with a unified text-to-text transformer. J. Mach. Learn. Res. 21(140), 1\u201367 (2020)","journal-title":"J. Mach. Learn. Res."},{"key":"11_CR20","unstructured":"Roziere, B., et\u00a0al.: Code LLaMA: open foundation models for code. arXiv preprint arXiv:2308.12950 (2023)"},{"key":"11_CR21","doi-asserted-by":"crossref","unstructured":"Shi, Y., Zhang, H., Wan, C., Gu, X.: Between lines of code: unraveling the distinct patterns of machine and human programmers. In: Proceedings of the 47th International Conference on Software Engineering (ICSE 2025). IEEE (2025)","DOI":"10.1109\/ICSE55347.2025.00005"},{"key":"11_CR22","doi-asserted-by":"crossref","unstructured":"Su, J., Zhuo, T.Y., Wang, D., Nakov, P.: DetectLLM: leveraging log rank information for zero-shot detection of machine-generated text. arXiv preprint arXiv:2306.05540 (2023)","DOI":"10.18653\/v1\/2023.findings-emnlp.827"},{"key":"11_CR23","unstructured":"Team, C., et\u00a0al.: CodeGemma: open code models based on Gemma. arXiv preprint arXiv:2406.11409 (2024)"},{"key":"11_CR24","unstructured":"Thomas, L.: Detecting fack content with relative entropy scoring. In: CEUR Workshop Proceedings, ECAI\u201908 Workshop on Plagiarism Analysis, Authorship Identification and Near-Duplication Detection, November, vol.\u00a0377, pp. 27\u201331 (2008)"},{"key":"11_CR25","unstructured":"Tunstall, L., et al.: Creating a coding assistant with StarCoder. Hugging Face Blog (2023). https:\/\/huggingface.co\/blog\/starchat-alpha"},{"key":"11_CR26","unstructured":"Vaswani, A., et al.: Attention is all you need. In: Advances in Neural Information Processing Systems, vol. 30 (2017)"},{"key":"11_CR27","doi-asserted-by":"crossref","unstructured":"Wang, Y., Wang, W., Joty, S., Hoi, S.C.: CodeT5: identifier-aware unified pre-trained encoder-decoder models for code understanding and generation. In: Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing (2021)","DOI":"10.18653\/v1\/2021.emnlp-main.685"},{"key":"11_CR28","unstructured":"Xu, J., et\u00a0al.: Investigating efficacy of perplexity in detecting LLM-generated code. arXiv preprint arXiv:2412.16525 (2024)"},{"key":"11_CR29","doi-asserted-by":"crossref","unstructured":"Xu, Z., Sheng, V.S.: Detecting ai-generated code assignments using perplexity of large language models. In: Proceedings of the AAAI Conference on Artificial Intelligence, vol. 38, issue (21), pp. 23155\u201323162 (2024)","DOI":"10.1609\/aaai.v38i21.30361"},{"key":"11_CR30","unstructured":"Yang, X., Cheng, W., Wu, Y., Petzold, L., Wang, W.Y., Chen, H.: DNA-GPT: divergent n-gram analysis for training-free detection of GPT-generated text. The Twelfth International Conference on Learning Representations (ICLR) (2024)"},{"key":"11_CR31","unstructured":"Yang, X., Zhang, K., Chen, H., Petzold, L., Wang, W.Y., Cheng, W.: Zero-shot detection of machine-generated codes. arXiv preprint arXiv:2310.05103 (2023)"},{"key":"11_CR32","doi-asserted-by":"crossref","unstructured":"Ye, T., et al.: Uncovering LLM-generated code: a zero-shot synthetic code detector via code rewriting. arXiv preprint arXiv:2405.16133 (2024)","DOI":"10.1609\/aaai.v39i1.32082"},{"key":"11_CR33","unstructured":"Yu, X., et al.: GPT paternity test: GPT generated text detection with GPT genetic inheritance. CoRR (2023)"},{"key":"11_CR34","unstructured":"Zellers, R., et al.: Defending against neural fake news. In: Advances in Neural Information Processing Systems, vol. 32 (2019)"},{"key":"11_CR35","doi-asserted-by":"crossref","unstructured":"Zhong, W., et al.: Neural deepfake detection with factual structure of text. In: Conference on Empirical Methods in Natural Language Processing (EMNLP) (2020)","DOI":"10.18653\/v1\/2020.emnlp-main.193"}],"container-title":["Lecture Notes in Computer Science","Machine Learning and Knowledge Discovery in Databases. Research Track"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-032-06078-5_11","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,9,29]],"date-time":"2025-09-29T18:50:29Z","timestamp":1759171829000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-032-06078-5_11"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,9,30]]},"ISBN":["9783032060778","9783032060785"],"references-count":35,"URL":"https:\/\/doi.org\/10.1007\/978-3-032-06078-5_11","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,9,30]]},"assertion":[{"value":"30 September 2025","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"The authors have no competing interests to declare that are relevant to the content of this article.","order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Disclosure of Interests"}},{"value":"ECML PKDD","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Joint European Conference on Machine Learning and Knowledge Discovery in Databases","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Porto","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Portugal","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2025","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"15 September 2025","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"19 September 2025","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"ecml2025","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/ecmlpkdd.org\/2025\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}