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A LLM Assisted Exploitation of AI-Guardian

A LLM Assisted Exploitation of AI-Guardian

20 July 2023
Nicholas Carlini
    ELM
    SILM
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Papers citing "A LLM Assisted Exploitation of AI-Guardian"

14 / 14 papers shown
Title
PaLM: Scaling Language Modeling with Pathways
PaLM: Scaling Language Modeling with Pathways
Aakanksha Chowdhery
Sharan Narang
Jacob Devlin
Maarten Bosma
Gaurav Mishra
...
Kathy Meier-Hellstern
Douglas Eck
J. Dean
Slav Petrov
Noah Fiedel
PILM
LRM
441
6,222
0
05 Apr 2022
Competition-Level Code Generation with AlphaCode
Competition-Level Code Generation with AlphaCode
Yujia Li
David Choi
Junyoung Chung
Nate Kushman
Julian Schrittwieser
...
Esme Sutherland Robson
Pushmeet Kohli
Nando de
Koray Kavukcuoglu
Oriol Vinyals
85
1,372
0
08 Feb 2022
Evading Adversarial Example Detection Defenses with Orthogonal Projected
  Gradient Descent
Evading Adversarial Example Detection Defenses with Orthogonal Projected Gradient Descent
Oliver Bryniarski
Nabeel Hingun
Pedro Pachuca
Vincent Wang
Nicholas Carlini
AAML
47
36
0
28 Jun 2021
On Adaptive Attacks to Adversarial Example Defenses
On Adaptive Attacks to Adversarial Example Defenses
Florian Tramèr
Nicholas Carlini
Wieland Brendel
Aleksander Madry
AAML
266
833
0
19 Feb 2020
On Evaluating Adversarial Robustness
On Evaluating Adversarial Robustness
Nicholas Carlini
Anish Athalye
Nicolas Papernot
Wieland Brendel
Jonas Rauber
Dimitris Tsipras
Ian Goodfellow
Aleksander Madry
Alexey Kurakin
ELM
AAML
81
901
0
18 Feb 2019
Certified Adversarial Robustness via Randomized Smoothing
Certified Adversarial Robustness via Randomized Smoothing
Jeremy M. Cohen
Elan Rosenfeld
J. Zico Kolter
AAML
132
2,036
0
08 Feb 2019
Certified Robustness to Adversarial Examples with Differential Privacy
Certified Robustness to Adversarial Examples with Differential Privacy
Mathias Lécuyer
Vaggelis Atlidakis
Roxana Geambasu
Daniel J. Hsu
Suman Jana
SILM
AAML
92
932
0
09 Feb 2018
Obfuscated Gradients Give a False Sense of Security: Circumventing
  Defenses to Adversarial Examples
Obfuscated Gradients Give a False Sense of Security: Circumventing Defenses to Adversarial Examples
Anish Athalye
Nicholas Carlini
D. Wagner
AAML
210
3,184
0
01 Feb 2018
Evasion Attacks against Machine Learning at Test Time
Evasion Attacks against Machine Learning at Test Time
Battista Biggio
Igino Corona
Davide Maiorca
B. Nelson
Nedim Srndic
Pavel Laskov
Giorgio Giacinto
Fabio Roli
AAML
155
2,147
0
21 Aug 2017
Towards Deep Learning Models Resistant to Adversarial Attacks
Towards Deep Learning Models Resistant to Adversarial Attacks
Aleksander Madry
Aleksandar Makelov
Ludwig Schmidt
Dimitris Tsipras
Adrian Vladu
SILM
OOD
292
12,060
0
19 Jun 2017
Adversarial Examples Are Not Easily Detected: Bypassing Ten Detection
  Methods
Adversarial Examples Are Not Easily Detected: Bypassing Ten Detection Methods
Nicholas Carlini
D. Wagner
AAML
118
1,857
0
20 May 2017
The Space of Transferable Adversarial Examples
The Space of Transferable Adversarial Examples
Florian Tramèr
Nicolas Papernot
Ian Goodfellow
Dan Boneh
Patrick McDaniel
AAML
SILM
82
558
0
11 Apr 2017
Towards Evaluating the Robustness of Neural Networks
Towards Evaluating the Robustness of Neural Networks
Nicholas Carlini
D. Wagner
OOD
AAML
252
8,550
0
16 Aug 2016
Intriguing properties of neural networks
Intriguing properties of neural networks
Christian Szegedy
Wojciech Zaremba
Ilya Sutskever
Joan Bruna
D. Erhan
Ian Goodfellow
Rob Fergus
AAML
259
14,912
1
21 Dec 2013
1