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A review of possible effects of cognitive biases on the interpretation
  of rule-based machine learning models

A review of possible effects of cognitive biases on the interpretation of rule-based machine learning models

9 April 2018
Tomáš Kliegr
Š. Bahník
Johannes Furnkranz
ArXivPDFHTML

Papers citing "A review of possible effects of cognitive biases on the interpretation of rule-based machine learning models"

6 / 6 papers shown
Title
T2VPhysBench: A First-Principles Benchmark for Physical Consistency in Text-to-Video Generation
T2VPhysBench: A First-Principles Benchmark for Physical Consistency in Text-to-Video Generation
Xuyang Guo
Jiayan Huo
Zhenmei Shi
Zhao Song
Jiahao Zhang
Jiale Zhao
EGVM
VGen
PINN
82
1
0
01 May 2025
Towards Unifying Evaluation of Counterfactual Explanations: Leveraging Large Language Models for Human-Centric Assessments
Towards Unifying Evaluation of Counterfactual Explanations: Leveraging Large Language Models for Human-Centric Assessments
M. Domnich
Julius Valja
Rasmus Moorits Veski
Giacomo Magnifico
Kadi Tulver
Eduard Barbu
Raul Vicente
LRM
ELM
48
2
0
28 Oct 2024
Explaining Predictions by Characteristic Rules
Explaining Predictions by Characteristic Rules
Amr Alkhatib
Henrik Bostrom
Michalis Vazirgiannis
29
5
0
31 May 2024
Interpretable Learned Emergent Communication for Human-Agent Teams
Interpretable Learned Emergent Communication for Human-Agent Teams
Seth Karten
Mycal Tucker
Huao Li
Siva Kailas
Michael Lewis
Katia P. Sycara
AI4CE
23
10
0
19 Jan 2022
Deciding Fast and Slow: The Role of Cognitive Biases in AI-assisted
  Decision-making
Deciding Fast and Slow: The Role of Cognitive Biases in AI-assisted Decision-making
Charvi Rastogi
Yunfeng Zhang
Dennis L. Wei
Kush R. Varshney
Amit Dhurandhar
Richard J. Tomsett
HAI
32
108
0
15 Oct 2020
The Pragmatic Turn in Explainable Artificial Intelligence (XAI)
The Pragmatic Turn in Explainable Artificial Intelligence (XAI)
Andrés Páez
8
190
0
22 Feb 2020
1