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A New Perspective on Evaluation Methods for Explainable Artificial
  Intelligence (XAI)

A New Perspective on Evaluation Methods for Explainable Artificial Intelligence (XAI)

26 July 2023
Timo Speith
Markus Langer
ArXivPDFHTML

Papers citing "A New Perspective on Evaluation Methods for Explainable Artificial Intelligence (XAI)"

6 / 6 papers shown
Title
What Does Evaluation of Explainable Artificial Intelligence Actually
  Tell Us? A Case for Compositional and Contextual Validation of XAI Building
  Blocks
What Does Evaluation of Explainable Artificial Intelligence Actually Tell Us? A Case for Compositional and Contextual Validation of XAI Building Blocks
Kacper Sokol
Julia E. Vogt
18
11
0
19 Mar 2024
Position: Explain to Question not to Justify
Position: Explain to Question not to Justify
Przemysław Biecek
Wojciech Samek
30
11
0
21 Feb 2024
Explainable Artificial Intelligence (XAI) 2.0: A Manifesto of Open
  Challenges and Interdisciplinary Research Directions
Explainable Artificial Intelligence (XAI) 2.0: A Manifesto of Open Challenges and Interdisciplinary Research Directions
Luca Longo
Mario Brcic
Federico Cabitza
Jaesik Choi
Roberto Confalonieri
...
Andrés Páez
Wojciech Samek
Johannes Schneider
Timo Speith
Simone Stumpf
24
186
0
30 Oct 2023
What Do We Want From Explainable Artificial Intelligence (XAI)? -- A
  Stakeholder Perspective on XAI and a Conceptual Model Guiding
  Interdisciplinary XAI Research
What Do We Want From Explainable Artificial Intelligence (XAI)? -- A Stakeholder Perspective on XAI and a Conceptual Model Guiding Interdisciplinary XAI Research
Markus Langer
Daniel Oster
Timo Speith
Holger Hermanns
Lena Kästner
Eva Schmidt
Andreas Sesing
Kevin Baum
XAI
43
411
0
15 Feb 2021
Formalizing Trust in Artificial Intelligence: Prerequisites, Causes and
  Goals of Human Trust in AI
Formalizing Trust in Artificial Intelligence: Prerequisites, Causes and Goals of Human Trust in AI
Alon Jacovi
Ana Marasović
Tim Miller
Yoav Goldberg
241
417
0
15 Oct 2020
Towards A Rigorous Science of Interpretable Machine Learning
Towards A Rigorous Science of Interpretable Machine Learning
Finale Doshi-Velez
Been Kim
XAI
FaML
225
3,658
0
28 Feb 2017
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