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L-AutoDA: Leveraging Large Language Models for Automated Decision-based
  Adversarial Attacks

L-AutoDA: Leveraging Large Language Models for Automated Decision-based Adversarial Attacks

27 January 2024
Ping Guo
Fei Liu
Xi Lin
Qingchuan Zhao
Qingfu Zhang
ArXivPDFHTML

Papers citing "L-AutoDA: Leveraging Large Language Models for Automated Decision-based Adversarial Attacks"

5 / 5 papers shown
Title
PuriDefense: Randomized Local Implicit Adversarial Purification for
  Defending Black-box Query-based Attacks
PuriDefense: Randomized Local Implicit Adversarial Purification for Defending Black-box Query-based Attacks
Ping Guo
Zhiyuan Yang
Xi Lin
Qingchuan Zhao
Qingfu Zhang
AAML
40
4
0
19 Jan 2024
Chip-Chat: Challenges and Opportunities in Conversational Hardware
  Design
Chip-Chat: Challenges and Opportunities in Conversational Hardware Design
Jason Blocklove
S. Garg
Ramesh Karri
Hammond Pearce
45
168
0
22 May 2023
AutoML-GPT: Automatic Machine Learning with GPT
AutoML-GPT: Automatic Machine Learning with GPT
Shujian Zhang
Chengyue Gong
Lemeng Wu
Xingchao Liu
Mi Zhou
LLMAG
67
60
0
04 May 2023
Stateful Defenses for Machine Learning Models Are Not Yet Secure Against
  Black-box Attacks
Stateful Defenses for Machine Learning Models Are Not Yet Secure Against Black-box Attacks
Ryan Feng
Ashish Hooda
Neal Mangaokar
Kassem Fawaz
S. Jha
Atul Prakash
AAML
63
11
0
11 Mar 2023
Sign-OPT: A Query-Efficient Hard-label Adversarial Attack
Sign-OPT: A Query-Efficient Hard-label Adversarial Attack
Minhao Cheng
Simranjit Singh
Patrick H. Chen
Pin-Yu Chen
Sijia Liu
Cho-Jui Hsieh
AAML
124
219
0
24 Sep 2019
1