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Extracting Training Data from Large Language Models


Dec 14, 2020
Nicholas Carlini, Florian Tramer, Eric Wallace, Matthew Jagielski, Ariel Herbert-Voss, Katherine Lee, Adam Roberts, Tom Brown, Dawn Song, Ulfar Erlingsson, Alina Oprea, Colin Raffel


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An Attack on InstaHide: Is Private Learning Possible with Instance Encoding?


Nov 10, 2020
Nicholas Carlini, Samuel Deng, Sanjam Garg, Somesh Jha, Saeed Mahloujifar, Mohammad Mahmoody, Shuang Song, Abhradeep Thakurta, Florian Tramer


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Label-Only Membership Inference Attacks


Jul 28, 2020
Christopher A. Choquette Choo, Florian Tramer, Nicholas Carlini, Nicolas Papernot

* 16 pages, 11 figures, 2 tables 

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On Adaptive Attacks to Adversarial Example Defenses


Feb 19, 2020
Florian Tramer, Nicholas Carlini, Wieland Brendel, Aleksander Madry


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Physical Adversarial Examples for Object Detectors


Oct 05, 2018
Kevin Eykholt, Ivan Evtimov, Earlence Fernandes, Bo Li, Amir Rahmati, Florian Tramer, Atul Prakash, Tadayoshi Kohno, Dawn Song

* This paper is the extended version of the USENIX WOOT 2018 version 

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Note on Attacking Object Detectors with Adversarial Stickers


Jul 23, 2018
Kevin Eykholt, Ivan Evtimov, Earlence Fernandes, Bo Li, Dawn Song, Tadayoshi Kohno, Amir Rahmati, Atul Prakash, Florian Tramer

* Short Note: The full version of this paper was accepted to USENIX WOOT 2018, and is available at arXiv:1807.07769 

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Slalom: Fast, Verifiable and Private Execution of Neural Networks in Trusted Hardware


Jun 08, 2018
Florian Tramer, Dan Boneh


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