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Auxiliary Losses for Learning Generalizable Concept-based Models

Auxiliary Losses for Learning Generalizable Concept-based Models

18 November 2023
Ivaxi Sheth
Samira Ebrahimi Kahou
ArXiv (abs)PDFHTML

Papers citing "Auxiliary Losses for Learning Generalizable Concept-based Models"

49 / 49 papers shown
Title
Leakage and Interpretability in Concept-Based Models
Leakage and Interpretability in Concept-Based Models
Enrico Parisini
Tapabrata Chakraborti
Chris Harbron
Ben D. MacArthur
Christopher R. S. Banerji
96
1
0
18 Apr 2025
Restyling Unsupervised Concept Based Interpretable Networks with Generative Models
Restyling Unsupervised Concept Based Interpretable Networks with Generative Models
Jayneel Parekh
Quentin Bouniot
Pavlo Mozharovskyi
A. Newson
Florence dÁlché-Buc
SSL
129
1
0
01 Jul 2024
Semi-supervised Concept Bottleneck Models
Semi-supervised Concept Bottleneck Models
Lijie Hu
Tianhao Huang
Huanyi Xie
Chenyang Ren
Zhengyu Hu
Lu Yu
Lu Yu
Ping Ma
Di Wang
123
8
0
27 Jun 2024
State2Explanation: Concept-Based Explanations to Benefit Agent Learning
  and User Understanding
State2Explanation: Concept-Based Explanations to Benefit Agent Learning and User Understanding
Devleena Das
Sonia Chernova
Been Kim
LRMLLMAG
85
24
0
21 Sep 2023
Probabilistic Concept Bottleneck Models
Probabilistic Concept Bottleneck Models
Eunji Kim
Dahuin Jung
Sangha Park
Siwon Kim
Sung-Hoon Yoon
121
70
0
02 Jun 2023
Label-Free Concept Bottleneck Models
Label-Free Concept Bottleneck Models
Tuomas P. Oikarinen
Subhro Das
Lam M. Nguyen
Tsui-Wei Weng
86
177
0
12 Apr 2023
Human Uncertainty in Concept-Based AI Systems
Human Uncertainty in Concept-Based AI Systems
Katherine M. Collins
Matthew Barker
M. Zarlenga
Naveen Raman
Umang Bhatt
M. Jamnik
Ilia Sucholutsky
Adrian Weller
Krishnamurthy Dvijotham
80
41
0
22 Mar 2023
A Closer Look at the Intervention Procedure of Concept Bottleneck Models
A Closer Look at the Intervention Procedure of Concept Bottleneck Models
Sungbin Shin
Yohan Jo
SungSoo Ahn
Namhoon Lee
72
34
0
28 Feb 2023
LLaMA: Open and Efficient Foundation Language Models
LLaMA: Open and Efficient Foundation Language Models
Hugo Touvron
Thibaut Lavril
Gautier Izacard
Xavier Martinet
Marie-Anne Lachaux
...
Faisal Azhar
Aurelien Rodriguez
Armand Joulin
Edouard Grave
Guillaume Lample
ALMPILM
1.5K
13,247
0
27 Feb 2023
SkinCon: A skin disease dataset densely annotated by domain experts for
  fine-grained model debugging and analysis
SkinCon: A skin disease dataset densely annotated by domain experts for fine-grained model debugging and analysis
Roxana Daneshjou
Mert Yuksekgonul
Zhuo Cai
R. Novoa
J. Zou
65
49
0
01 Feb 2023
Towards Robust Metrics for Concept Representation Evaluation
Towards Robust Metrics for Concept Representation Evaluation
M. Zarlenga
Pietro Barbiero
Z. Shams
Dmitry Kazhdan
Umang Bhatt
Adrian Weller
M. Jamnik
48
24
0
25 Jan 2023
Interactive Concept Bottleneck Models
Interactive Concept Bottleneck Models
Kushal Chauhan
Rishabh Tiwari
Jan Freyberg
Pradeep Shenoy
Krishnamurthy Dvijotham
56
55
0
14 Dec 2022
Concept Embedding Models: Beyond the Accuracy-Explainability Trade-Off
Concept Embedding Models: Beyond the Accuracy-Explainability Trade-Off
M. Zarlenga
Pietro Barbiero
Gabriele Ciravegna
G. Marra
Francesco Giannini
...
F. Precioso
S. Melacci
Adrian Weller
Pietro Lio
M. Jamnik
126
59
0
19 Sep 2022
Monitoring Shortcut Learning using Mutual Information
Monitoring Shortcut Learning using Mutual Information
Mohammed Adnan
Yani Andrew Ioannou
Chuan-Yung Tsai
A. Galloway
H. R. Tizhoosh
Graham W. Taylor
55
6
0
27 Jun 2022
Post-hoc Concept Bottleneck Models
Post-hoc Concept Bottleneck Models
Mert Yuksekgonul
Maggie Wang
James Zou
215
196
0
31 May 2022
Concept Bottleneck Model with Additional Unsupervised Concepts
Concept Bottleneck Model with Additional Unsupervised Concepts
Yoshihide Sawada
Keigo Nakamura
SSL
62
73
0
03 Feb 2022
A Framework for Learning Ante-hoc Explainable Models via Concepts
A Framework for Learning Ante-hoc Explainable Models via Concepts
Anirban Sarkar
Deepak Vijaykeerthy
Anindya Sarkar
V. Balasubramanian
LRMBDL
81
50
0
25 Aug 2021
Promises and Pitfalls of Black-Box Concept Learning Models
Promises and Pitfalls of Black-Box Concept Learning Models
Anita Mahinpei
Justin Clark
Isaac Lage
Finale Doshi-Velez
Weiwei Pan
83
96
0
24 Jun 2021
Do Concept Bottleneck Models Learn as Intended?
Do Concept Bottleneck Models Learn as Intended?
Andrei Margeloiu
Matthew Ashman
Umang Bhatt
Yanzhi Chen
M. Jamnik
Adrian Weller
SLR
50
97
0
10 May 2021
Orthogonalizing Convolutional Layers with the Cayley Transform
Orthogonalizing Convolutional Layers with the Cayley Transform
Asher Trockman
J. Zico Kolter
64
114
0
14 Apr 2021
Orthogonal Projection Loss
Orthogonal Projection Loss
Kanchana Ranasinghe
Muzammal Naseer
Munawar Hayat
Salman Khan
Fahad Shahbaz Khan
VLM
58
72
0
25 Mar 2021
Learning Transferable Visual Models From Natural Language Supervision
Learning Transferable Visual Models From Natural Language Supervision
Alec Radford
Jong Wook Kim
Chris Hallacy
Aditya A. Ramesh
Gabriel Goh
...
Amanda Askell
Pamela Mishkin
Jack Clark
Gretchen Krueger
Ilya Sutskever
CLIPVLM
964
29,731
0
26 Feb 2021
Explainability of deep vision-based autonomous driving systems: Review
  and challenges
Explainability of deep vision-based autonomous driving systems: Review and challenges
Éloi Zablocki
H. Ben-younes
P. Pérez
Matthieu Cord
XAI
132
173
0
13 Jan 2021
An Image is Worth 16x16 Words: Transformers for Image Recognition at
  Scale
An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale
Alexey Dosovitskiy
Lucas Beyer
Alexander Kolesnikov
Dirk Weissenborn
Xiaohua Zhai
...
Matthias Minderer
G. Heigold
Sylvain Gelly
Jakob Uszkoreit
N. Houlsby
ViT
664
41,103
0
22 Oct 2020
Concept Bottleneck Models
Concept Bottleneck Models
Pang Wei Koh
Thao Nguyen
Y. S. Tang
Stephen Mussmann
Emma Pierson
Been Kim
Percy Liang
99
828
0
09 Jul 2020
Language Models are Few-Shot Learners
Language Models are Few-Shot Learners
Tom B. Brown
Benjamin Mann
Nick Ryder
Melanie Subbiah
Jared Kaplan
...
Christopher Berner
Sam McCandlish
Alec Radford
Ilya Sutskever
Dario Amodei
BDL
817
42,055
0
28 May 2020
Shortcut Learning in Deep Neural Networks
Shortcut Learning in Deep Neural Networks
Robert Geirhos
J. Jacobsen
Claudio Michaelis
R. Zemel
Wieland Brendel
Matthias Bethge
Felix Wichmann
211
2,052
0
16 Apr 2020
Concept Whitening for Interpretable Image Recognition
Concept Whitening for Interpretable Image Recognition
Zhi Chen
Yijie Bei
Cynthia Rudin
FAtt
78
322
0
05 Feb 2020
Benchmarking Robustness in Object Detection: Autonomous Driving when
  Winter is Coming
Benchmarking Robustness in Object Detection: Autonomous Driving when Winter is Coming
Claudio Michaelis
Benjamin Mitzkus
Robert Geirhos
E. Rusak
Oliver Bringmann
Alexander S. Ecker
Matthias Bethge
Wieland Brendel
3DPC
99
445
0
17 Jul 2019
Invariant Risk Minimization
Invariant Risk Minimization
Martín Arjovsky
Léon Bottou
Ishaan Gulrajani
David Lopez-Paz
OOD
192
2,241
0
05 Jul 2019
Benchmarking Neural Network Robustness to Common Corruptions and
  Perturbations
Benchmarking Neural Network Robustness to Common Corruptions and Perturbations
Dan Hendrycks
Thomas G. Dietterich
OODVLM
188
3,445
0
28 Mar 2019
Global Explanations of Neural Networks: Mapping the Landscape of
  Predictions
Global Explanations of Neural Networks: Mapping the Landscape of Predictions
Mark Ibrahim
Melissa Louie
C. Modarres
John Paisley
FAtt
66
118
0
06 Feb 2019
Local Explanation Methods for Deep Neural Networks Lack Sensitivity to
  Parameter Values
Local Explanation Methods for Deep Neural Networks Lack Sensitivity to Parameter Values
Julius Adebayo
Justin Gilmer
Ian Goodfellow
Been Kim
FAttAAML
49
128
0
08 Oct 2018
Sanity Checks for Saliency Maps
Sanity Checks for Saliency Maps
Julius Adebayo
Justin Gilmer
M. Muelly
Ian Goodfellow
Moritz Hardt
Been Kim
FAttAAMLXAI
141
1,967
0
08 Oct 2018
A Review of Challenges and Opportunities in Machine Learning for Health
A Review of Challenges and Opportunities in Machine Learning for Health
Marzyeh Ghassemi
Tristan Naumann
Peter F. Schulam
Andrew L. Beam
Irene Y. Chen
Rajesh Ranganath
70
268
0
01 Jun 2018
Interpretability Beyond Feature Attribution: Quantitative Testing with
  Concept Activation Vectors (TCAV)
Interpretability Beyond Feature Attribution: Quantitative Testing with Concept Activation Vectors (TCAV)
Been Kim
Martin Wattenberg
Justin Gilmer
Carrie J. Cai
James Wexler
F. Viégas
Rory Sayres
FAtt
217
1,842
0
30 Nov 2017
Contrastive-center loss for deep neural networks
Contrastive-center loss for deep neural networks
Ce Qi
Fei Su
SSL
48
71
0
24 Jul 2017
Zero-Shot Learning -- A Comprehensive Evaluation of the Good, the Bad
  and the Ugly
Zero-Shot Learning -- A Comprehensive Evaluation of the Good, the Bad and the Ugly
Yongqin Xian
Christoph H. Lampert
Bernt Schiele
Zeynep Akata
VLM
162
1,568
0
03 Jul 2017
Methods for Interpreting and Understanding Deep Neural Networks
Methods for Interpreting and Understanding Deep Neural Networks
G. Montavon
Wojciech Samek
K. Müller
FaML
291
2,266
0
24 Jun 2017
Attention Is All You Need
Attention Is All You Need
Ashish Vaswani
Noam M. Shazeer
Niki Parmar
Jakob Uszkoreit
Llion Jones
Aidan Gomez
Lukasz Kaiser
Illia Polosukhin
3DV
713
132,199
0
12 Jun 2017
On orthogonality and learning recurrent networks with long term
  dependencies
On orthogonality and learning recurrent networks with long term dependencies
Eugene Vorontsov
C. Trabelsi
Samuel Kadoury
C. Pal
ODL
84
241
0
31 Jan 2017
Grad-CAM: Visual Explanations from Deep Networks via Gradient-based
  Localization
Grad-CAM: Visual Explanations from Deep Networks via Gradient-based Localization
Ramprasaath R. Selvaraju
Michael Cogswell
Abhishek Das
Ramakrishna Vedantam
Devi Parikh
Dhruv Batra
FAtt
321
20,023
0
07 Oct 2016
Layer-wise Relevance Propagation for Neural Networks with Local
  Renormalization Layers
Layer-wise Relevance Propagation for Neural Networks with Local Renormalization Layers
Alexander Binder
G. Montavon
Sebastian Lapuschkin
K. Müller
Wojciech Samek
FAtt
77
462
0
04 Apr 2016
Deep Residual Learning for Image Recognition
Deep Residual Learning for Image Recognition
Kaiming He
Xinming Zhang
Shaoqing Ren
Jian Sun
MedIm
2.2K
194,020
0
10 Dec 2015
Rethinking the Inception Architecture for Computer Vision
Rethinking the Inception Architecture for Computer Vision
Christian Szegedy
Vincent Vanhoucke
Sergey Ioffe
Jonathon Shlens
Z. Wojna
3DVBDL
883
27,373
0
02 Dec 2015
End-to-End Attention-based Large Vocabulary Speech Recognition
End-to-End Attention-based Large Vocabulary Speech Recognition
Dzmitry Bahdanau
J. Chorowski
Dmitriy Serdyuk
Philemon Brakel
Yoshua Bengio
82
1,152
0
18 Aug 2015
Dropout as a Bayesian Approximation: Representing Model Uncertainty in
  Deep Learning
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning
Y. Gal
Zoubin Ghahramani
UQCVBDL
829
9,345
0
06 Jun 2015
FaceNet: A Unified Embedding for Face Recognition and Clustering
FaceNet: A Unified Embedding for Face Recognition and Clustering
Florian Schroff
Dmitry Kalenichenko
James Philbin
3DH
379
13,145
0
12 Mar 2015
Exact solutions to the nonlinear dynamics of learning in deep linear
  neural networks
Exact solutions to the nonlinear dynamics of learning in deep linear neural networks
Andrew M. Saxe
James L. McClelland
Surya Ganguli
ODL
178
1,849
0
20 Dec 2013
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