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Dimensions underlying the representational alignment of deep neural networks with humans

Dimensions underlying the representational alignment of deep neural networks with humans

Nature Machine Intelligence (Nat. Mach. Intell.), 2024
28 January 2025
F. Mahner
Lukas Muttenthaler
Umut Güçlü
M. Hebart
ArXiv (abs)PDFHTMLGithub (14★)

Papers citing "Dimensions underlying the representational alignment of deep neural networks with humans"

42 / 42 papers shown
Learning Fourier shapes to probe the geometric world of deep neural networks
Learning Fourier shapes to probe the geometric world of deep neural networks
Jian Wang
Yixing Yong
Haixia Bi
Lijun He
Fan Li
AAML
267
0
0
07 Nov 2025
Bridging the behavior-neural gap: A multimodal AI reveals the brain's geometry of emotion more accurately than human self-reports
Bridging the behavior-neural gap: A multimodal AI reveals the brain's geometry of emotion more accurately than human self-reports
Changde Du
Yizhuo Lu
Zhongyu Huang
Yi Sun
Zisen Zhou
Shaozheng Qin
Huiguang He
123
0
0
29 Sep 2025
Experience Scaling: Post-Deployment Evolution For Large Language Models
Experience Scaling: Post-Deployment Evolution For Large Language Models
Xingkun Yin
Kaibin Huang
Dong In Kim
Hongyang Du
168
0
0
23 Sep 2025
Disentangling the Factors of Convergence between Brains and Computer Vision Models
Disentangling the Factors of Convergence between Brains and Computer Vision Models
Joséphine Raugel
Marc Szafraniec
Huy V. Vo
Camille Couprie
Patrick Labatut
Piotr Bojanowski
Valentin Wyart
Jean-Rémi King
149
12
0
25 Aug 2025
Synthesizing Images on Perceptual Boundaries of ANNs for Uncovering Human Perceptual Variability on Facial Expressions
Synthesizing Images on Perceptual Boundaries of ANNs for Uncovering Human Perceptual Variability on Facial Expressions
Haotian Deng
Chi Zhang
Chen Wei
Quanying Liu
174
0
0
19 Jul 2025
Seeing What Tastes Good: Revisiting Multimodal Distributional Semantics in the Billion Parameter Era
Seeing What Tastes Good: Revisiting Multimodal Distributional Semantics in the Billion Parameter EraAnnual Meeting of the Association for Computational Linguistics (ACL), 2025
Dan Oneaţă
Desmond Elliott
Stella Frank
235
3
0
04 Jun 2025
Investigating Fine- and Coarse-grained Structural Correspondences Between Deep Neural Networks and Human Object Image Similarity Judgments Using Unsupervised Alignment
Investigating Fine- and Coarse-grained Structural Correspondences Between Deep Neural Networks and Human Object Image Similarity Judgments Using Unsupervised AlignmentNeural Networks (NN), 2025
Soh Takahashi
Masaru Sasaki
Ken Takeda
Masafumi Oizumi
247
4
0
22 May 2025
LVD-2M: A Long-take Video Dataset with Temporally Dense Captions
LVD-2M: A Long-take Video Dataset with Temporally Dense CaptionsNeural Information Processing Systems (NeurIPS), 2024
Tianwei Xiong
Yuqing Wang
Daquan Zhou
Zhijie Lin
Jiashi Feng
Xihui Liu
VGen
315
16
0
14 Oct 2024
Human-like object concept representations emerge naturally in multimodal large language models
Human-like object concept representations emerge naturally in multimodal large language models
Changde Du
Kaicheng Fu
Bincheng Wen
Yi Sun
Jie Peng
...
Chuncheng Zhang
Jinpeng Li
Shuang Qiu
Le Chang
Huiguang He
576
30
0
01 Jul 2024
On the Foundations of Shortcut Learning
On the Foundations of Shortcut LearningInternational Conference on Learning Representations (ICLR), 2023
Katherine Hermann
Hossein Mobahi
Thomas Fel
M. C. Mozer
VLM
508
69
0
24 Oct 2023
Getting aligned on representational alignment
Getting aligned on representational alignment
Ilia Sucholutsky
Lukas Muttenthaler
Adrian Weller
Andi Peng
Andreea Bobu
...
Thomas Unterthiner
Andrew Kyle Lampinen
Klaus-Robert Muller
M. Toneva
Thomas Griffiths
396
153
0
18 Oct 2023
Don't trust your eyes: on the (un)reliability of feature visualizations
Don't trust your eyes: on the (un)reliability of feature visualizationsInternational Conference on Machine Learning (ICML), 2023
Robert Geirhos
Roland S. Zimmermann
Blair Bilodeau
Wieland Brendel
Been Kim
FAttOOD
548
38
0
07 Jun 2023
Improving neural network representations using human similarity
  judgments
Improving neural network representations using human similarity judgmentsNeural Information Processing Systems (NeurIPS), 2023
Lukas Muttenthaler
Lorenz Linhardt
Jonas Dippel
Robert A. Vandermeulen
Katherine L. Hermann
Andrew Kyle Lampinen
Simon Kornblith
349
48
0
07 Jun 2023
Harmonizing the object recognition strategies of deep neural networks
  with humans
Harmonizing the object recognition strategies of deep neural networks with humansNeural Information Processing Systems (NeurIPS), 2022
Thomas Fel
Ivan Felipe
Drew Linsley
Thomas Serre
429
103
0
08 Nov 2022
VICE: Variational Interpretable Concept Embeddings
VICE: Variational Interpretable Concept EmbeddingsNeural Information Processing Systems (NeurIPS), 2022
Lukas Muttenthaler
C. Zheng
Patrick McClure
Robert A. Vandermeulen
M. Hebart
Francisco Câmara Pereira
540
17
0
02 May 2022
StyleGAN-XL: Scaling StyleGAN to Large Diverse Datasets
StyleGAN-XL: Scaling StyleGAN to Large Diverse DatasetsInternational Conference on Computer Graphics and Interactive Techniques (SIGGRAPH), 2022
Axel Sauer
Katja Schwarz
Andreas Geiger
1.2K
659
0
01 Feb 2022
Transforming Neural Network Visual Representations to Predict Human
  Judgments of Similarity
Transforming Neural Network Visual Representations to Predict Human Judgments of Similarity
Maria Attarian
Brett D. Roads
Michael C. Mozer
254
22
0
13 Oct 2020
Understanding the Role of Individual Units in a Deep Neural Network
Understanding the Role of Individual Units in a Deep Neural NetworkProceedings of the National Academy of Sciences of the United States of America (PNAS), 2020
David Bau
Jun-Yan Zhu
Hendrik Strobelt
Àgata Lapedriza
Bolei Zhou
Antonio Torralba
GAN
436
514
0
10 Sep 2020
Shortcut Learning in Deep Neural Networks
Shortcut Learning in Deep Neural NetworksNature Machine Intelligence (NMI), 2020
Robert Geirhos
J. Jacobsen
Claudio Michaelis
R. Zemel
Wieland Brendel
Matthias Bethge
Felix Wichmann
1.5K
2,717
0
16 Apr 2020
Convolutional Neural Networks as a Model of the Visual System: Past,
  Present, and Future
Convolutional Neural Networks as a Model of the Visual System: Past, Present, and FutureJournal of Cognitive Neuroscience (J Cogn Neurosci), 2020
Grace W. Lindsay
MedIm
371
502
0
20 Jan 2020
Learning as the Unsupervised Alignment of Conceptual Systems
Learning as the Unsupervised Alignment of Conceptual SystemsNature Machine Intelligence (NMI), 2019
Brett D. Roads
Bradley C. Love
OCL
410
50
0
21 Jun 2019
Similarity of Neural Network Representations Revisited
Similarity of Neural Network Representations RevisitedInternational Conference on Machine Learning (ICML), 2019
Simon Kornblith
Mohammad Norouzi
Honglak Lee
Geoffrey E. Hinton
1.5K
1,963
0
01 May 2019
Representation Similarity Analysis for Efficient Task taxonomy &
  Transfer Learning
Representation Similarity Analysis for Efficient Task taxonomy & Transfer Learning
Kshitij Dwivedi
Gemma Roig
212
165
0
26 Apr 2019
Understanding Neural Networks via Feature Visualization: A survey
Understanding Neural Networks via Feature Visualization: A survey
Anh Nguyen
J. Yosinski
Jeff Clune
FAtt
282
173
0
18 Apr 2019
Revealing interpretable object representations from human behavior
Revealing interpretable object representations from human behavior
C. Zheng
Francisco Câmara Pereira
C. Baker
M. Hebart
OCL
189
44
0
09 Jan 2019
ImageNet-trained CNNs are biased towards texture; increasing shape bias
  improves accuracy and robustness
ImageNet-trained CNNs are biased towards texture; increasing shape bias improves accuracy and robustness
Robert Geirhos
Patricia Rubisch
Claudio Michaelis
Matthias Bethge
Felix Wichmann
Wieland Brendel
1.0K
3,058
0
29 Nov 2018
Generalisation in humans and deep neural networks
Generalisation in humans and deep neural networks
Robert Geirhos
Carlos R. Medina Temme
Jonas Rauber
Heiko H. Schutt
Matthias Bethge
Felix Wichmann
OOD
515
669
0
27 Aug 2018
Recognition in Terra Incognita
Recognition in Terra Incognita
Sara Beery
Grant Van Horn
Pietro Perona
636
1,050
0
13 Jul 2018
Revisiting the Importance of Individual Units in CNNs via Ablation
Revisiting the Importance of Individual Units in CNNs via Ablation
Bolei Zhou
Yiyou Sun
David Bau
Antonio Torralba
FAtt
361
127
0
07 Jun 2018
On the importance of single directions for generalization
On the importance of single directions for generalization
Ari S. Morcos
David Barrett
Neil C. Rabinowitz
M. Botvinick
634
352
0
19 Mar 2018
Methods for Interpreting and Understanding Deep Neural Networks
Methods for Interpreting and Understanding Deep Neural Networks
G. Montavon
Wojciech Samek
K. Müller
FaML
680
2,498
0
24 Jun 2017
Network Dissection: Quantifying Interpretability of Deep Visual
  Representations
Network Dissection: Quantifying Interpretability of Deep Visual Representations
David Bau
Bolei Zhou
A. Khosla
A. Oliva
Antonio Torralba
MILMFAtt
746
1,710
1
19 Apr 2017
Grad-CAM: Visual Explanations from Deep Networks via Gradient-based
  Localization
Grad-CAM: Visual Explanations from Deep Networks via Gradient-based LocalizationInternational Journal of Computer Vision (IJCV), 2016
Ramprasaath R. Selvaraju
Michael Cogswell
Abhishek Das
Ramakrishna Vedantam
Devi Parikh
Dhruv Batra
FAtt
1.1K
26,025
0
07 Oct 2016
De-Conflated Semantic Representations
De-Conflated Semantic Representations
Mohammad Taher Pilehvar
Nigel Collier
NAI
153
93
0
05 Aug 2016
Finite Sample Prediction and Recovery Bounds for Ordinal Embedding
Finite Sample Prediction and Recovery Bounds for Ordinal EmbeddingNeural Information Processing Systems (NeurIPS), 2016
Lalit P. Jain
Kevin Jamieson
Robert D. Nowak
299
76
0
22 Jun 2016
Deep Residual Learning for Image Recognition
Deep Residual Learning for Image Recognition
Kaiming He
Xinming Zhang
Shaoqing Ren
Jian Sun
MedIm
4.2K
225,080
0
10 Dec 2015
Deep Speech 2: End-to-End Speech Recognition in English and Mandarin
Deep Speech 2: End-to-End Speech Recognition in English and Mandarin
Dario Amodei
Rishita Anubhai
Eric Battenberg
Carl Case
Jared Casper
...
Chong-Jun Wang
Bo Xiao
Dani Yogatama
J. Zhan
Zhenyao Zhu
1.6K
3,130
0
08 Dec 2015
Understanding Neural Networks Through Deep Visualization
Understanding Neural Networks Through Deep Visualization
J. Yosinski
Jeff Clune
Anh Totti Nguyen
Thomas J. Fuchs
Hod Lipson
FAttAI4CE
757
1,936
0
22 Jun 2015
Understanding Deep Image Representations by Inverting Them
Understanding Deep Image Representations by Inverting ThemComputer Vision and Pattern Recognition (CVPR), 2014
Aravindh Mahendran
Andrea Vedaldi
FAtt
696
2,066
0
26 Nov 2014
Very Deep Convolutional Networks for Large-Scale Image Recognition
Very Deep Convolutional Networks for Large-Scale Image RecognitionInternational Conference on Learning Representations (ICLR), 2014
Karen Simonyan
Andrew Zisserman
FAttMDE
4.0K
110,590
0
04 Sep 2014
Intriguing properties of neural networks
Intriguing properties of neural networksInternational Conference on Learning Representations (ICLR), 2013
Christian Szegedy
Wojciech Zaremba
Ilya Sutskever
Joan Bruna
D. Erhan
Ian Goodfellow
Rob Fergus
AAML
1.4K
16,393
1
21 Dec 2013
Visualizing and Understanding Convolutional Networks
Visualizing and Understanding Convolutional NetworksEuropean Conference on Computer Vision (ECCV), 2013
Matthew D. Zeiler
Rob Fergus
FAttSSL
1.3K
16,902
0
12 Nov 2013
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