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ELUDE: Generating interpretable explanations via a decomposition into
  labelled and unlabelled features

ELUDE: Generating interpretable explanations via a decomposition into labelled and unlabelled features

15 June 2022
V. V. Ramaswamy
Sunnie S. Y. Kim
Nicole Meister
Ruth C. Fong
Olga Russakovsky
    FAtt
ArXivPDFHTML

Papers citing "ELUDE: Generating interpretable explanations via a decomposition into labelled and unlabelled features"

5 / 5 papers shown
Title
Interactivity x Explainability: Toward Understanding How Interactivity Can Improve Computer Vision Explanations
Interactivity x Explainability: Toward Understanding How Interactivity Can Improve Computer Vision Explanations
Indu Panigrahi
Sunnie S. Y. Kim
Amna Liaqat
Rohan Jinturkar
Olga Russakovsky
Ruth C. Fong
Parastoo Abtahi
FAtt
HAI
57
0
0
14 Apr 2025
UFO: A unified method for controlling Understandability and Faithfulness
  Objectives in concept-based explanations for CNNs
UFO: A unified method for controlling Understandability and Faithfulness Objectives in concept-based explanations for CNNs
V. V. Ramaswamy
Sunnie S. Y. Kim
Ruth C. Fong
Olga Russakovsky
35
0
0
27 Mar 2023
Take 5: Interpretable Image Classification with a Handful of Features
Take 5: Interpretable Image Classification with a Handful of Features
Thomas Norrenbrock
Marco Rudolph
Bodo Rosenhahn
FAtt
42
7
0
23 Mar 2023
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
66
114
0
06 Dec 2021
Semantic Understanding of Scenes through the ADE20K Dataset
Semantic Understanding of Scenes through the ADE20K Dataset
Bolei Zhou
Hang Zhao
Xavier Puig
Tete Xiao
Sanja Fidler
Adela Barriuso
Antonio Torralba
SSeg
253
1,829
0
18 Aug 2016
1