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Towards Human-centered Explainable AI: A Survey of User Studies for
  Model Explanations

Towards Human-centered Explainable AI: A Survey of User Studies for Model Explanations

20 October 2022
Yao Rong
Tobias Leemann
Thai-trang Nguyen
Lisa Fiedler
Peizhu Qian
Vaibhav Unhelkar
Tina Seidel
Gjergji Kasneci
Enkelejda Kasneci
    ELM
ArXivPDFHTML

Papers citing "Towards Human-centered Explainable AI: A Survey of User Studies for Model Explanations"

21 / 21 papers shown
Title
Exploring the Impact of Explainable AI and Cognitive Capabilities on Users' Decisions
Exploring the Impact of Explainable AI and Cognitive Capabilities on Users' Decisions
Federico Maria Cau
Lucio Davide Spano
22
0
0
02 May 2025
Enhancing Job Salary Prediction with Disentangled Composition Effect Modeling: A Neural Prototyping Approach
Enhancing Job Salary Prediction with Disentangled Composition Effect Modeling: A Neural Prototyping Approach
Yang Ji
Ying Sun
Hengshu Zhu
46
0
0
17 Mar 2025
Class-Dependent Perturbation Effects in Evaluating Time Series Attributions
Class-Dependent Perturbation Effects in Evaluating Time Series Attributions
Gregor Baer
Isel Grau
Chao Zhang
Pieter Van Gorp
AAML
41
0
0
24 Feb 2025
Attention Mechanisms Don't Learn Additive Models: Rethinking Feature Importance for Transformers
Attention Mechanisms Don't Learn Additive Models: Rethinking Feature Importance for Transformers
Tobias Leemann
Alina Fastowski
Felix Pfeiffer
Gjergji Kasneci
51
4
0
10 Jan 2025
GPT for Games: An Updated Scoping Review (2020-2024)
GPT for Games: An Updated Scoping Review (2020-2024)
Daijin Yang
Erica Kleinman
Casper Harteveld
LLMAG
AI4TS
AI4CE
44
2
0
01 Nov 2024
Efficient and Accurate Explanation Estimation with Distribution Compression
Efficient and Accurate Explanation Estimation with Distribution Compression
Hubert Baniecki
Giuseppe Casalicchio
Bernd Bischl
Przemyslaw Biecek
FAtt
34
3
0
26 Jun 2024
Inpainting the Gaps: A Novel Framework for Evaluating Explanation
  Methods in Vision Transformers
Inpainting the Gaps: A Novel Framework for Evaluating Explanation Methods in Vision Transformers
Lokesh Badisa
Sumohana S. Channappayya
32
0
0
17 Jun 2024
Selective Explanations
Selective Explanations
Lucas Monteiro Paes
Dennis L. Wei
Flavio du Pin Calmon
FAtt
25
0
0
29 May 2024
I-CEE: Tailoring Explanations of Image Classification Models to User
  Expertise
I-CEE: Tailoring Explanations of Image Classification Models to User Expertise
Yao Rong
Peizhu Qian
Vaibhav Unhelkar
Enkelejda Kasneci
17
0
0
19 Dec 2023
Sparks of Artificial General Intelligence: Early experiments with GPT-4
Sparks of Artificial General Intelligence: Early experiments with GPT-4
Sébastien Bubeck
Varun Chandrasekaran
Ronen Eldan
J. Gehrke
Eric Horvitz
...
Scott M. Lundberg
Harsha Nori
Hamid Palangi
Marco Tulio Ribeiro
Yi Zhang
ELM
AI4MH
AI4CE
ALM
206
2,232
0
22 Mar 2023
The Utility of Explainable AI in Ad Hoc Human-Machine Teaming
The Utility of Explainable AI in Ad Hoc Human-Machine Teaming
Rohan R. Paleja
Muyleng Ghuy
Nadun R. Arachchige
Reed Jensen
Matthew C. Gombolay
68
62
0
08 Sep 2022
A Psychological Theory of Explainability
A Psychological Theory of Explainability
Scott Cheng-Hsin Yang
Tomas Folke
Patrick Shafto
XAI
FAtt
36
15
0
17 May 2022
Chain-of-Thought Prompting Elicits Reasoning in Large Language Models
Chain-of-Thought Prompting Elicits Reasoning in Large Language Models
Jason W. Wei
Xuezhi Wang
Dale Schuurmans
Maarten Bosma
Brian Ichter
F. Xia
Ed H. Chi
Quoc Le
Denny Zhou
LM&Ro
LRM
AI4CE
ReLM
315
8,261
0
28 Jan 2022
Human Interpretation of Saliency-based Explanation Over Text
Human Interpretation of Saliency-based Explanation Over Text
Hendrik Schuff
Alon Jacovi
Heike Adel
Yoav Goldberg
Ngoc Thang Vu
MILM
XAI
FAtt
144
38
0
27 Jan 2022
HIVE: Evaluating the Human Interpretability of Visual Explanations
HIVE: Evaluating the Human Interpretability of Visual Explanations
Sunnie S. Y. Kim
Nicole Meister
V. V. Ramaswamy
Ruth C. Fong
Olga Russakovsky
58
112
0
06 Dec 2021
Intuitively Assessing ML Model Reliability through Example-Based
  Explanations and Editing Model Inputs
Intuitively Assessing ML Model Reliability through Example-Based Explanations and Editing Model Inputs
Harini Suresh
Kathleen M. Lewis
John Guttag
Arvind Satyanarayan
FAtt
32
25
0
17 Feb 2021
Evaluating the Interpretability of Generative Models by Interactive
  Reconstruction
Evaluating the Interpretability of Generative Models by Interactive Reconstruction
A. Ross
Nina Chen
Elisa Zhao Hang
Elena L. Glassman
Finale Doshi-Velez
92
49
0
02 Feb 2021
Artificial Intelligence Methods in In-Cabin Use Cases: A Survey
Artificial Intelligence Methods in In-Cabin Use Cases: A Survey
Yao Rong
Chao Han
Christian Hellert
Antje Loyal
Enkelejda Kasneci
22
16
0
06 Jan 2021
On Completeness-aware Concept-Based Explanations in Deep Neural Networks
On Completeness-aware Concept-Based Explanations in Deep Neural Networks
Chih-Kuan Yeh
Been Kim
Sercan Ö. Arik
Chun-Liang Li
Tomas Pfister
Pradeep Ravikumar
FAtt
120
293
0
17 Oct 2019
Methods for Interpreting and Understanding Deep Neural Networks
Methods for Interpreting and Understanding Deep Neural Networks
G. Montavon
Wojciech Samek
K. Müller
FaML
228
2,231
0
24 Jun 2017
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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