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Publication search results
found 91 matches
- 2024
- Ilia Shumailov, Zakhar Shumaylov, Yiren Zhao, Nicolas Papernot, Ross J. Anderson, Yarin Gal:
AI models collapse when trained on recursively generated data. Nat. 631(8022): 755-759 (2024) - Anvith Thudi, Ilia Shumailov, Franziska Boenisch, Nicolas Papernot:
From Differential Privacy to Bounds on Membership Inference: Less can be More. Trans. Mach. Learn. Res. 2024 (2024) - Sierra Calanda Wyllie, Ilia Shumailov, Nicolas Papernot:
Fairness Feedback Loops: Training on Synthetic Data Amplifies Bias. FAccT 2024: 2113-2147 - David Glukhov, Ilia Shumailov, Yarin Gal, Nicolas Papernot, Vardan Papyan:
Position: Fundamental Limitations of LLM Censorship Necessitate New Approaches. ICML 2024 - Eleanor Clifford, Ilia Shumailov, Yiren Zhao, Ross J. Anderson, Robert D. Mullins:
ImpNet: Imperceptible and blackbox-undetectable backdoors in compiled neural networks. SaTML 2024: 344-357 - Pranav Dahiya, Ilia Shumailov, Ross Anderson:
Machine Learning needs Better Randomness Standards: Randomised Smoothing and PRNG-based attacks. USENIX Security Symposium 2024 - Anvith Thudi, Hengrui Jia, Casey Meehan, Ilia Shumailov, Nicolas Papernot:
Gradients Look Alike: Sensitivity is Often Overestimated in DP-SGD. USENIX Security Symposium 2024 - Jamie Hayes, Ilia Shumailov, Itay Yona:
Buffer Overflow in Mixture of Experts. CoRR abs/2402.05526 (2024) - Harry Langford, Ilia Shumailov, Yiren Zhao, Robert D. Mullins, Nicolas Papernot:
Architectural Neural Backdoors from First Principles. CoRR abs/2402.06957 (2024) - Jamie Hayes, Ilia Shumailov, Eleni Triantafillou, Amr Khalifa, Nicolas Papernot:
Inexact Unlearning Needs More Careful Evaluations to Avoid a False Sense of Privacy. CoRR abs/2403.01218 (2024) - Sierra Calanda Wyllie, Ilia Shumailov, Nicolas Papernot:
Fairness Feedback Loops: Training on Synthetic Data Amplifies Bias. CoRR abs/2403.07857 (2024) - Eleanor Clifford, Adhithya Saravanan, Harry Langford, Cheng Zhang, Yiren Zhao, Robert D. Mullins, Ilia Shumailov, Jamie Hayes:
Locking Machine Learning Models into Hardware. CoRR abs/2405.20990 (2024) - Hanna Foerster, Robert D. Mullins, Ilia Shumailov, Jamie Hayes:
Beyond Slow Signs in High-fidelity Model Extraction. CoRR abs/2406.10011 (2024) - Aneesh Pappu, Billy Porter, Ilia Shumailov, Jamie Hayes:
Measuring memorization in RLHF for code completion. CoRR abs/2406.11715 (2024) - Ilia Shumailov, Jamie Hayes, Eleni Triantafillou, Guillermo Ortiz-Jiménez, Nicolas Papernot, Matthew Jagielski, Itay Yona, Heidi Howard, Eugene Bagdasaryan:
UnUnlearning: Unlearning is not sufficient for content regulation in advanced generative AI. CoRR abs/2407.00106 (2024) - David Glukhov, Ziwen Han, Ilia Shumailov, Vardan Papyan, Nicolas Papernot:
A False Sense of Safety: Unsafe Information Leakage in 'Safe' AI Responses. CoRR abs/2407.02551 (2024) - Sahra Ghalebikesabi, Eugene Bagdasaryan, Ren Yi, Itay Yona, Ilia Shumailov, Aneesh Pappu, Chongyang Shi, Laura Weidinger, Robert Stanforth, Leonard Berrada, Pushmeet Kohli, Po-Sen Huang, Borja Balle:
Operationalizing Contextual Integrity in Privacy-Conscious Assistants. CoRR abs/2408.02373 (2024) - 2023
- Yulin Zhou, Yiren Zhao, Ilia Shumailov, Robert D. Mullins, Yarin Gal:
Revisiting Automated Prompting: Are We Actually Doing Better? ACL (2) 2023: 1822-1832 - Mikel Bober-Irizar, Ilia Shumailov, Yiren Zhao, Robert D. Mullins, Nicolas Papernot:
Architectural Backdoors in Neural Networks. CVPR 2023: 24595-24604 - Cheng Zhang, Jianyi Cheng, Ilia Shumailov, George A. Constantinides, Yiren Zhao:
Revisiting Block-based Quantisation: What is Important for Sub-8-bit LLM Inference? EMNLP 2023: 9988-10006 - Franziska Boenisch, Adam Dziedzic, Roei Schuster, Ali Shahin Shamsabadi, Ilia Shumailov, Nicolas Papernot:
When the Curious Abandon Honesty: Federated Learning Is Not Private. EuroS&P 2023: 175-199 - Franziska Boenisch, Adam Dziedzic, Roei Schuster, Ali Shahin Shamsabadi, Ilia Shumailov, Nicolas Papernot:
Reconstructing Individual Data Points in Federated Learning Hardened with Differential Privacy and Secure Aggregation. EuroS&P 2023: 241-257 - Nicholas Boucher, Luca Pajola, Ilia Shumailov, Ross J. Anderson, Mauro Conti:
Boosting Big Brother: Attacking Search Engines with Encodings. RAID 2023: 700-713 - Shimaa Ahmed, Yash Wani, Ali Shahin Shamsabadi, Mohammad Yaghini, Ilia Shumailov, Nicolas Papernot, Kassem Fawaz:
Tubes Among Us: Analog Attack on Automatic Speaker Identification. USENIX Security Symposium 2023: 265-282 - Franziska Boenisch, Adam Dziedzic, Roei Schuster, Ali Shahin Shamsabadi, Ilia Shumailov, Nicolas Papernot:
Is Federated Learning a Practical PET Yet? CoRR abs/2301.04017 (2023) - Yulin Zhou, Yiren Zhao, Ilia Shumailov, Robert D. Mullins, Yarin Gal:
Revisiting Automated Prompting: Are We Actually Doing Better? CoRR abs/2304.03609 (2023) - Nicholas Boucher, Luca Pajola, Ilia Shumailov, Ross J. Anderson, Mauro Conti:
Boosting Big Brother: Attacking Search Engines with Encodings. CoRR abs/2304.14031 (2023) - Ilia Shumailov, Zakhar Shumaylov, Yiren Zhao, Yarin Gal, Nicolas Papernot, Ross J. Anderson:
The Curse of Recursion: Training on Generated Data Makes Models Forget. CoRR abs/2305.17493 (2023) - Nicholas Boucher, Jenny Blessing, Ilia Shumailov, Ross Anderson, Nicolas Papernot:
When Vision Fails: Text Attacks Against ViT and OCR. CoRR abs/2306.07033 (2023) - Pranav Dahiya, Ilia Shumailov, Ross J. Anderson:
Machine Learning needs its own Randomness Standard: Randomised Smoothing and PRNG-based attacks. CoRR abs/2306.14043 (2023)
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