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Shortcomings of Top-Down Randomization-Based Sanity Checks for
  Evaluations of Deep Neural Network Explanations

Shortcomings of Top-Down Randomization-Based Sanity Checks for Evaluations of Deep Neural Network Explanations

22 November 2022
Alexander Binder
Leander Weber
Sebastian Lapuschkin
G. Montavon
Klaus-Robert Muller
Wojciech Samek
    FAtt
    AAML
ArXivPDFHTML

Papers citing "Shortcomings of Top-Down Randomization-Based Sanity Checks for Evaluations of Deep Neural Network Explanations"

7 / 7 papers shown
Title
On the Evaluation Consistency of Attribution-based Explanations
On the Evaluation Consistency of Attribution-based Explanations
Jiarui Duan
Haoling Li
Haofei Zhang
Hao Jiang
Mengqi Xue
Li Sun
Mingli Song
Mingli Song
XAI
46
1
0
28 Jul 2024
A Fresh Look at Sanity Checks for Saliency Maps
A Fresh Look at Sanity Checks for Saliency Maps
Anna Hedström
Leander Weber
Sebastian Lapuschkin
Marina M.-C. Höhne
FAtt
LRM
48
5
0
03 May 2024
Respect the model: Fine-grained and Robust Explanation with Sharing
  Ratio Decomposition
Respect the model: Fine-grained and Robust Explanation with Sharing Ratio Decomposition
Sangyu Han
Yearim Kim
Nojun Kwak
AAML
29
1
0
25 Jan 2024
Preemptively Pruning Clever-Hans Strategies in Deep Neural Networks
Preemptively Pruning Clever-Hans Strategies in Deep Neural Networks
Lorenz Linhardt
Klaus-Robert Muller
G. Montavon
AAML
26
7
0
12 Apr 2023
The Meta-Evaluation Problem in Explainable AI: Identifying Reliable
  Estimators with MetaQuantus
The Meta-Evaluation Problem in Explainable AI: Identifying Reliable Estimators with MetaQuantus
Anna Hedström
P. Bommer
Kristoffer K. Wickstrom
Wojciech Samek
Sebastian Lapuschkin
Marina M.-C. Höhne
37
21
0
14 Feb 2023
DORA: Exploring Outlier Representations in Deep Neural Networks
DORA: Exploring Outlier Representations in Deep Neural Networks
Kirill Bykov
Mayukh Deb
Dennis Grinwald
Klaus-Robert Muller
Marina M.-C. Höhne
27
12
0
09 Jun 2022
Methods for Interpreting and Understanding Deep Neural Networks
Methods for Interpreting and Understanding Deep Neural Networks
G. Montavon
Wojciech Samek
K. Müller
FaML
234
2,238
0
24 Jun 2017
1