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Human-in-the-Loop Interpretability Prior

Human-in-the-Loop Interpretability Prior

29 May 2018
Isaac Lage
A. Ross
Been Kim
S. Gershman
Finale Doshi-Velez
ArXivPDFHTML

Papers citing "Human-in-the-Loop Interpretability Prior"

14 / 14 papers shown
Title
A New Perspective on Evaluation Methods for Explainable Artificial
  Intelligence (XAI)
A New Perspective on Evaluation Methods for Explainable Artificial Intelligence (XAI)
Timo Speith
Markus Langer
22
12
0
26 Jul 2023
Perspectives on Incorporating Expert Feedback into Model Updates
Perspectives on Incorporating Expert Feedback into Model Updates
Valerie Chen
Umang Bhatt
Hoda Heidari
Adrian Weller
Ameet Talwalkar
30
11
0
13 May 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
26
9
0
12 Apr 2022
Debiased-CAM to mitigate systematic error with faithful visual explanations of machine learning
Wencan Zhang
Mariella Dimiccoli
Brian Y. Lim
FAtt
15
1
0
30 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
114
0
06 Dec 2021
Self-Interpretable Model with TransformationEquivariant Interpretation
Self-Interpretable Model with TransformationEquivariant Interpretation
Yipei Wang
Xiaoqian Wang
24
23
0
09 Nov 2021
Interactive Dimensionality Reduction for Comparative Analysis
Interactive Dimensionality Reduction for Comparative Analysis
Takanori Fujiwara
Xinhai Wei
Jian Zhao
K. Ma
17
30
0
29 Jun 2021
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
26
65
0
23 Jun 2021
Sequential Explanations with Mental Model-Based Policies
Sequential Explanations with Mental Model-Based Policies
A. Yeung
Shalmali Joshi
Joseph Jay Williams
Frank Rudzicz
FAtt
LRM
23
15
0
17 Jul 2020
On Interpretability of Artificial Neural Networks: A Survey
On Interpretability of Artificial Neural Networks: A Survey
Fenglei Fan
Jinjun Xiong
Mengzhou Li
Ge Wang
AAML
AI4CE
30
300
0
08 Jan 2020
When Explanations Lie: Why Many Modified BP Attributions Fail
When Explanations Lie: Why Many Modified BP Attributions Fail
Leon Sixt
Maximilian Granz
Tim Landgraf
BDL
FAtt
XAI
11
132
0
20 Dec 2019
Interpretable Models for Understanding Immersive Simulations
Interpretable Models for Understanding Immersive Simulations
Nicholas Hoernle
Yaákov Gal
Barbara J. Grosz
Leilah Lyons
Ada Ren
Andee Rubin
8
4
0
24 Sep 2019
Learning Representations by Humans, for Humans
Learning Representations by Humans, for Humans
Sophie Hilgard
Nir Rosenfeld
M. Banaji
Jack Cao
David C. Parkes
OCL
HAI
AI4CE
26
29
0
29 May 2019
Scalable agent alignment via reward modeling: a research direction
Scalable agent alignment via reward modeling: a research direction
Jan Leike
David M. Krueger
Tom Everitt
Miljan Martic
Vishal Maini
Shane Legg
12
392
0
19 Nov 2018
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