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2103.03386
Cited By
Clusterability in Neural Networks
4 March 2021
Daniel Filan
Stephen Casper
Shlomi Hod
Cody Wild
Andrew Critch
Stuart J. Russell
GNN
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Papers citing
"Clusterability in Neural Networks"
20 / 20 papers shown
How LLMs Learn to Reason: A Complex Network Perspective
Sihan Hu
X-D Cai
Yuan Huang
Zhiyuan Yao
Linfeng Zhang
Pan Zhang
Youjin Deng
Kun Chen
LRM
269
2
0
28 Sep 2025
Evaluating Explanations: An Explanatory Virtues Framework for Mechanistic Interpretability -- The Strange Science Part I.ii
Kola Ayonrinde
Louis Jaburi
XAI
377
3
0
02 May 2025
Studying Cross-cluster Modularity in Neural Networks
Satvik Golechha
Maheep Chaudhary
Joan Velja
Alessandro Abate
Nandi Schoots
434
0
0
04 Feb 2025
Differentiation and Specialization of Attention Heads via the Refined Local Learning Coefficient
International Conference on Learning Representations (ICLR), 2024
George Wang
Jesse Hoogland
Stan van Wingerden
Zach Furman
Daniel Murfet
OffRL
285
28
0
03 Oct 2024
Training Neural Networks for Modularity aids Interpretability
Satvik Golechha
Dylan R. Cope
Nandi Schoots
338
1
0
24 Sep 2024
Modularity in Deep Learning: A Survey
Haozhe Sun
Isabelle Guyon
MoMe
358
7
0
02 Oct 2023
Neural Sculpting: Uncovering hierarchically modular task structure in neural networks through pruning and network analysis
Neural Information Processing Systems (NeurIPS), 2023
S. M. Patil
Loizos Michael
C. Dovrolis
282
0
0
28 May 2023
Understanding Sparse Neural Networks from their Topology via Multipartite Graph Representations
Elia Cunegatti
Matteo Farina
Doina Bucur
Giovanni Iacca
373
3
0
26 May 2023
Seeing is Believing: Brain-Inspired Modular Training for Mechanistic Interpretability
Ziming Liu
Eric Gan
Max Tegmark
280
56
0
04 May 2023
AI Model Utilization Measurements For Finding Class Encoding Patterns
P. Bajcsy
Antonio Cardone
Chenyi Ling
Philippe Dessauw
Michael Majurski
Timothy Blattner
D. Juba
Walid Keyrouz
155
0
0
12 Dec 2022
Modular Federated Learning
IEEE International Joint Conference on Neural Network (IJCNN), 2022
Kuo-Yun Liang
A. Srinivasan
J. C. Andresen
FedML
344
7
0
07 Sep 2022
Toward Transparent AI: A Survey on Interpreting the Inner Structures of Deep Neural Networks
Tilman Raukur
A. Ho
Stephen Casper
Dylan Hadfield-Menell
AAML
AI4CE
861
182
0
27 Jul 2022
Auditing Visualizations: Transparency Methods Struggle to Detect Anomalous Behavior
Jean-Stanislas Denain
Jacob Steinhardt
AAML
348
7
0
27 Jun 2022
Pruning for Feature-Preserving Circuits in CNNs
Christopher Hamblin
Talia Konkle
G. Alvarez
363
3
0
03 Jun 2022
Clustering units in neural networks: upstream vs downstream information
Richard D. Lange
David Rolnick
Konrad Paul Kording
171
12
0
22 Mar 2022
Leveraging the Graph Structure of Neural Network Training Dynamics
International Conference on Information and Knowledge Management (CIKM), 2021
Fatemeh Vahedian
Ruiyu Li
Puja Trivedi
Di Jin
Danai Koutra
AI4CE
GNN
242
3
0
09 Nov 2021
Quantifying Local Specialization in Deep Neural Networks
Shlomi Hod
Daniel Filan
Stephen Casper
Andrew Critch
Stuart J. Russell
380
13
0
13 Oct 2021
Visual Representation Learning Does Not Generalize Strongly Within the Same Domain
International Conference on Learning Representations (ICLR), 2021
Lukas Schott
Julius von Kügelgen
Frederik Trauble
Peter V. Gehler
Chris Russell
Matthias Bethge
Bernhard Schölkopf
Francesco Locatello
Wieland Brendel
OOD
DRL
453
79
0
17 Jul 2021
Modularity in Reinforcement Learning via Algorithmic Independence in Credit Assignment
International Conference on Machine Learning (ICML), 2021
Michael Chang
Sid Kaushik
Sergey Levine
Thomas Griffiths
296
8
0
28 Jun 2021
Dynamics of specialization in neural modules under resource constraints
Nature Communications (Nat Commun), 2021
Gabriel Béna
Dan F. M. Goodman
378
9
0
04 Jun 2021
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