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MINIMAL: Mining Models for Data Free Universal Adversarial Triggers

MINIMAL: Mining Models for Data Free Universal Adversarial Triggers

25 September 2021
Swapnil Parekh
Yaman Kumar Singla
Somesh Singh
Changyou Chen
Balaji Krishnamurthy
R. Shah
    AAML
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Papers citing "MINIMAL: Mining Models for Data Free Universal Adversarial Triggers"

4 / 4 papers shown
Title
Why do universal adversarial attacks work on large language models?:
  Geometry might be the answer
Why do universal adversarial attacks work on large language models?: Geometry might be the answer
Varshini Subhash
Anna Bialas
Weiwei Pan
Finale Doshi-Velez
AAML
22
10
0
01 Sep 2023
Data-Free Adversarial Perturbations for Practical Black-Box Attack
Data-Free Adversarial Perturbations for Practical Black-Box Attack
Zhaoxin Huan
Yulong Wang
Xiaolu Zhang
L. Shang
Chilin Fu
Jun Zhou
20
12
0
03 Mar 2020
Hypothesis Only Baselines in Natural Language Inference
Hypothesis Only Baselines in Natural Language Inference
Adam Poliak
Jason Naradowsky
Aparajita Haldar
Rachel Rudinger
Benjamin Van Durme
190
576
0
02 May 2018
A Decomposable Attention Model for Natural Language Inference
A Decomposable Attention Model for Natural Language Inference
Ankur P. Parikh
Oscar Täckström
Dipanjan Das
Jakob Uszkoreit
213
1,367
0
06 Jun 2016
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