ResearchTrend.AI
  • Communities
  • Connect sessions
  • AI calendar
  • Organizations
  • Join Slack
  • Contact Sales
Papers
Communities
Social Events
Terms and Conditions
Pricing
Contact Sales
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2026 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 2211.14860
  4. Cited By
Foiling Explanations in Deep Neural Networks
v1v2v3 (latest)

Foiling Explanations in Deep Neural Networks

27 November 2022
Snir Vitrack Tamam
Raz Lapid
Moshe Sipper
    AAML
ArXiv (abs)PDFHTML

Papers citing "Foiling Explanations in Deep Neural Networks"

13 / 13 papers shown
Don't Lag, RAG: Training-Free Adversarial Detection Using RAG
Don't Lag, RAG: Training-Free Adversarial Detection Using RAG
Roie Kazoom
Raz Lapid
Moshe Sipper
Ofer Hadar
VLMObjDAAML
416
5
0
07 Apr 2025
On the Robustness of Kolmogorov-Arnold Networks: An Adversarial Perspective
On the Robustness of Kolmogorov-Arnold Networks: An Adversarial Perspective
Tal Alter
Raz Lapid
Moshe Sipper
AAML
474
14
0
25 Aug 2024
Evolutionary Computation and Explainable AI: A Roadmap to Transparent
  Intelligent Systems
Evolutionary Computation and Explainable AI: A Roadmap to Transparent Intelligent Systems
Ryan Zhou
Jaume Bacardit
Alexander Brownlee
Stefano Cagnoni
Martin Fyvie
Giovanni Iacca
John Mccall
Niki van Stein
David Walker
Ting-Kuei Hu
236
1
0
12 Jun 2024
Fortify the Guardian, Not the Treasure: Resilient Adversarial Detectors
Fortify the Guardian, Not the Treasure: Resilient Adversarial Detectors
Raz Lapid
Almog Dubin
Moshe Sipper
AAML
229
6
0
18 Apr 2024
Are Classification Robustness and Explanation Robustness Really Strongly
  Correlated? An Analysis Through Input Loss Landscape
Are Classification Robustness and Explanation Robustness Really Strongly Correlated? An Analysis Through Input Loss Landscape
Tiejin Chen
Wenwang Huang
Linsey Pang
Dongsheng Luo
Hua Wei
OOD
259
0
0
09 Mar 2024
XAI-Based Detection of Adversarial Attacks on Deepfake Detectors
XAI-Based Detection of Adversarial Attacks on Deepfake Detectors
Ben Pinhasov
Raz Lapid
Rony Ohayon
Moshe Sipper
Y. Aperstein
AAML
190
15
0
05 Mar 2024
Open Sesame! Universal Black Box Jailbreaking of Large Language Models
Open Sesame! Universal Black Box Jailbreaking of Large Language ModelsApplied Sciences (Appl. Sci.), 2023
Raz Lapid
Ron Langberg
Moshe Sipper
AAML
343
151
0
04 Sep 2023
Evolutionary approaches to explainable machine learning
Evolutionary approaches to explainable machine learning
Ryan Zhou
Ting-Kuei Hu
238
10
0
23 Jun 2023
I See Dead People: Gray-Box Adversarial Attack on Image-To-Text Models
I See Dead People: Gray-Box Adversarial Attack on Image-To-Text Models
Raz Lapid
Moshe Sipper
AAML
233
24
0
13 Jun 2023
A Melting Pot of Evolution and Learning
A Melting Pot of Evolution and LearningGenetic Programming Theory and Practice (GPTP), 2023
Moshe Sipper
Achiya Elyasaf
Tomer Halperin
Zvika Haramaty
Raz Lapid
Eyal Segal
Itai Tzruia
Snir Vitrack Tamam
BDL
128
0
0
08 Jun 2023
Adversarial attacks and defenses in explainable artificial intelligence: A survey
Adversarial attacks and defenses in explainable artificial intelligence: A surveyInformation Fusion (Inf. Fusion), 2023
Hubert Baniecki
P. Biecek
AAML
523
116
0
06 Jun 2023
Patch of Invisibility: Naturalistic Physical Black-Box Adversarial
  Attacks on Object Detectors
Patch of Invisibility: Naturalistic Physical Black-Box Adversarial Attacks on Object Detectors
Raz Lapid
Eylon Mizrahi
Moshe Sipper
AAML
361
3
0
07 Mar 2023
When and How to Fool Explainable Models (and Humans) with Adversarial
  Examples
When and How to Fool Explainable Models (and Humans) with Adversarial Examples
Jon Vadillo
Roberto Santana
Jose A. Lozano
SILMAAML
264
21
0
05 Jul 2021
1