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To trust or not to trust an explanation: using LEAF to evaluate local
  linear XAI methods

To trust or not to trust an explanation: using LEAF to evaluate local linear XAI methods

1 June 2021
E. Amparore
Alan Perotti
P. Bajardi
    FAtt
ArXivPDFHTML

Papers citing "To trust or not to trust an explanation: using LEAF to evaluate local linear XAI methods"

11 / 11 papers shown
Title
T-Explainer: A Model-Agnostic Explainability Framework Based on Gradients
T-Explainer: A Model-Agnostic Explainability Framework Based on Gradients
Evandro S. Ortigossa
Fábio F. Dias
Brian Barr
Claudio T. Silva
L. G. Nonato
FAtt
61
2
0
25 Apr 2024
Trust Regions for Explanations via Black-Box Probabilistic Certification
Trust Regions for Explanations via Black-Box Probabilistic Certification
Amit Dhurandhar
Swagatam Haldar
Dennis L. Wei
K. Ramamurthy
FAtt
40
2
0
17 Feb 2024
Precise Benchmarking of Explainable AI Attribution Methods
Precise Benchmarking of Explainable AI Attribution Methods
Rafael Brandt
Daan Raatjens
G. Gaydadjiev
XAI
27
4
0
06 Aug 2023
REVEL Framework to measure Local Linear Explanations for black-box
  models: Deep Learning Image Classification case of study
REVEL Framework to measure Local Linear Explanations for black-box models: Deep Learning Image Classification case of study
Iván Sevillano-García
Julián Luengo-Martín
Francisco Herrera
XAI
FAtt
21
7
0
11 Nov 2022
Local Interpretable Model Agnostic Shap Explanations for machine
  learning models
Local Interpretable Model Agnostic Shap Explanations for machine learning models
P. Aditya
M. Pal
FAtt
34
6
0
10 Oct 2022
RESHAPE: Explaining Accounting Anomalies in Financial Statement Audits
  by enhancing SHapley Additive exPlanations
RESHAPE: Explaining Accounting Anomalies in Financial Statement Audits by enhancing SHapley Additive exPlanations
Ricardo Müller
Marco Schreyer
Timur Sattarov
Damian Borth
AAML
MLAU
35
7
0
19 Sep 2022
Explainable Intrusion Detection Systems (X-IDS): A Survey of Current
  Methods, Challenges, and Opportunities
Explainable Intrusion Detection Systems (X-IDS): A Survey of Current Methods, Challenges, and Opportunities
Subash Neupane
Jesse Ables
William Anderson
Sudip Mittal
Shahram Rahimi
I. Banicescu
Maria Seale
AAML
56
71
0
13 Jul 2022
Enriching Artificial Intelligence Explanations with Knowledge Fragments
Enriching Artificial Intelligence Explanations with Knowledge Fragments
Jože M. Rožanec
Elena Trajkova
I. Novalija
Patrik Zajec
K. Kenda
B. Fortuna
Dunja Mladenić
28
9
0
12 Apr 2022
Synthetic Benchmarks for Scientific Research in Explainable Machine
  Learning
Synthetic Benchmarks for Scientific Research in Explainable Machine Learning
Yang Liu
Sujay Khandagale
Colin White
W. Neiswanger
37
65
0
23 Jun 2021
How Well do Feature Visualizations Support Causal Understanding of CNN
  Activations?
How Well do Feature Visualizations Support Causal Understanding of CNN Activations?
Roland S. Zimmermann
Judy Borowski
Robert Geirhos
Matthias Bethge
Thomas S. A. Wallis
Wieland Brendel
FAtt
47
31
0
23 Jun 2021
Probing GNN Explainers: A Rigorous Theoretical and Empirical Analysis of
  GNN Explanation Methods
Probing GNN Explainers: A Rigorous Theoretical and Empirical Analysis of GNN Explanation Methods
Chirag Agarwal
Marinka Zitnik
Himabindu Lakkaraju
27
51
0
16 Jun 2021
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