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Classification Metrics for Image Explanations: Towards Building Reliable
  XAI-Evaluations

Classification Metrics for Image Explanations: Towards Building Reliable XAI-Evaluations

7 June 2024
Benjamin Frész
Lena Lörcher
Marco F. Huber
ArXiv (abs)PDFHTMLGithub (2★)

Papers citing "Classification Metrics for Image Explanations: Towards Building Reliable XAI-Evaluations"

14 / 14 papers shown
Title
Sanity Checks for Saliency Methods Explaining Object Detectors
Sanity Checks for Saliency Methods Explaining Object Detectors
Deepan Padmanabhan
Paul G. Plöger
Octavio Arriaga
Matias Valdenegro-Toro
FAttAAMLXAI
50
2
0
04 Jun 2023
OpenXAI: Towards a Transparent Evaluation of Model Explanations
OpenXAI: Towards a Transparent Evaluation of Model Explanations
Chirag Agarwal
Dan Ley
Satyapriya Krishna
Eshika Saxena
Martin Pawelczyk
Nari Johnson
Isha Puri
Marinka Zitnik
Himabindu Lakkaraju
XAI
71
147
0
22 Jun 2022
Towards Better Understanding Attribution Methods
Towards Better Understanding Attribution Methods
Sukrut Rao
Moritz Bohle
Bernt Schiele
XAI
63
33
0
20 May 2022
Quantus: An Explainable AI Toolkit for Responsible Evaluation of Neural
  Network Explanations and Beyond
Quantus: An Explainable AI Toolkit for Responsible Evaluation of Neural Network Explanations and Beyond
Anna Hedström
Leander Weber
Dilyara Bareeva
Daniel G. Krakowczyk
Franz Motzkus
Wojciech Samek
Sebastian Lapuschkin
Marina M.-C. Höhne
XAIELM
56
178
0
14 Feb 2022
From Anecdotal Evidence to Quantitative Evaluation Methods: A Systematic
  Review on Evaluating Explainable AI
From Anecdotal Evidence to Quantitative Evaluation Methods: A Systematic Review on Evaluating Explainable AI
Meike Nauta
Jan Trienes
Shreyasi Pathak
Elisa Nguyen
Michelle Peters
Yasmin Schmitt
Jorg Schlotterer
M. V. Keulen
C. Seifert
ELMXAI
125
418
0
20 Jan 2022
Sanity Checks for Saliency Metrics
Sanity Checks for Saliency Metrics
Richard J. Tomsett
Daniel Harborne
Supriyo Chakraborty
Prudhvi K. Gurram
Alun D. Preece
XAI
100
170
0
29 Nov 2019
Sanity Checks for Saliency Maps
Sanity Checks for Saliency Maps
Julius Adebayo
Justin Gilmer
M. Muelly
Ian Goodfellow
Moritz Hardt
Been Kim
FAttAAMLXAI
146
1,969
0
08 Oct 2018
The (Un)reliability of saliency methods
The (Un)reliability of saliency methods
Pieter-Jan Kindermans
Sara Hooker
Julius Adebayo
Maximilian Alber
Kristof T. Schütt
Sven Dähne
D. Erhan
Been Kim
FAttXAI
104
688
0
02 Nov 2017
Grad-CAM++: Improved Visual Explanations for Deep Convolutional Networks
Grad-CAM++: Improved Visual Explanations for Deep Convolutional Networks
Aditya Chattopadhyay
Anirban Sarkar
Prantik Howlader
V. Balasubramanian
FAtt
112
2,306
0
30 Oct 2017
A Unified Approach to Interpreting Model Predictions
A Unified Approach to Interpreting Model Predictions
Scott M. Lundberg
Su-In Lee
FAtt
1.1K
22,018
0
22 May 2017
Axiomatic Attribution for Deep Networks
Axiomatic Attribution for Deep Networks
Mukund Sundararajan
Ankur Taly
Qiqi Yan
OODFAtt
193
6,018
0
04 Mar 2017
Layer-wise Relevance Propagation for Neural Networks with Local
  Renormalization Layers
Layer-wise Relevance Propagation for Neural Networks with Local Renormalization Layers
Alexander Binder
G. Montavon
Sebastian Lapuschkin
K. Müller
Wojciech Samek
FAtt
77
462
0
04 Apr 2016
"Why Should I Trust You?": Explaining the Predictions of Any Classifier
"Why Should I Trust You?": Explaining the Predictions of Any Classifier
Marco Tulio Ribeiro
Sameer Singh
Carlos Guestrin
FAttFaML
1.2K
17,033
0
16 Feb 2016
Very Deep Convolutional Networks for Large-Scale Image Recognition
Very Deep Convolutional Networks for Large-Scale Image Recognition
Karen Simonyan
Andrew Zisserman
FAttMDE
1.7K
100,508
0
04 Sep 2014
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