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Who cites «Privacy Risk in Machine Learning: Analyzing the Connection to Overfitting»

86 papers of our library cite it (of the 149,439 whose bibliographies we read) · 22 with a page here, the most cited first · ← back to «Privacy Risk in Machine Learning: Analyzing the Connection to Overfitting»

  1. Extracting Training Data from Large Language ModelsarXiv:2012.07805Nicholas Carlini, Florian Tramer, Eric Wallace, et al.2020 · 955 citations
  2. The Secret Sharer: Evaluating and Testing Unintended Memorization in Neural NetworksarXiv:1802.08232Nicholas Carlini, Chang Liu, Ulfar Erlingsson, et al.2018 · 692 citations
  3. Security and Privacy Challenges of Large Language Models: A SurveyACM Computing SurveysBadhan Chandra Das, M. Hadi Amini, Yanzhao Wu2024 · 424 citations
  4. Trustworthy LLMs: a Survey and Guideline for Evaluating Large Language Models' AlignmentarXiv:2308.05374Yang Liu; Yuanshun Yao; Jean-Francois Ton; Xiaoying Zhang; Ruocheng Guo; Hao Cheng; Yegor Klochkov; Muhammad Faaiz Taufiq;, Hang Li2023 · 223 citations
  5. Scalable Extraction of Training Data from (Production) Language ModelsarXiv:2311.17035Milad Nasr, Nicholas Carlini, Jonathan Hayase, et al.2023 · 211 citations
  6. Deduplicating Training Data Mitigates Privacy Risks in Language ModelsarXiv:2202.06539Nikhil Kandpal, Eric Wallace, Colin Raffel2022 · 172 citations
  7. Do Membership Inference Attacks Work on Large Language Models?arXiv:2402.07841Michael Duan, Anshuman Suri, Niloofar Mireshghallah, et al.2024 · 87 citations

64 more papers of our library cite it; they have no page here yet.

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