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The Lottery Ticket Hypothesis: Finding Sparse, Trainable Neural Networks
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The Lottery Ticket Hypothesis: Finding Sparse, Trainable Neural Networks

9 March 2018
Jonathan Frankle
Michael Carbin
ArXiv (abs)PDFHTML

Papers citing "The Lottery Ticket Hypothesis: Finding Sparse, Trainable Neural Networks"

50 / 2,186 papers shown
Finding Stable Subnetworks at Initialization with Dataset Distillation
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Staying Alive: Online Neural Network Maintenance and Systemic Drift
Staying Alive: Online Neural Network Maintenance and Systemic Drift
Joshua Edward Hammond
Tyler Soderstrom
Brian A. Korgel
Michael Baldea
203
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22 Mar 2025
Temporal Action Detection Model Compression by Progressive Block Drop
Temporal Action Detection Model Compression by Progressive Block DropComputer Vision and Pattern Recognition (CVPR), 2025
Xiaoyong Chen
Yong Guo
Jiaming Liang
Sitong Zhuang
Runhao Zeng
Xiping Hu
302
1
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21 Mar 2025
Structure Is Not Enough: Leveraging Behavior for Neural Network Weight Reconstruction
Structure Is Not Enough: Leveraging Behavior for Neural Network Weight Reconstruction
Léo Meynent
Ivan Melev
Konstantin Schurholt
Göran Kauermann
Damian Borth
369
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0
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LoRASculpt: Sculpting LoRA for Harmonizing General and Specialized Knowledge in Multimodal Large Language Models
LoRASculpt: Sculpting LoRA for Harmonizing General and Specialized Knowledge in Multimodal Large Language ModelsComputer Vision and Pattern Recognition (CVPR), 2025
Jian Liang
Wenke Huang
Guancheng Wan
Qu Yang
Mang Ye
MoMeCLLAI4CE
320
11
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FeNeC: Enhancing Continual Learning via Feature Clustering with Neighbor- or Logit-Based Classification
FeNeC: Enhancing Continual Learning via Feature Clustering with Neighbor- or Logit-Based Classification
Kamil Książek
Hubert Jastrzębski
Bartosz Trojan
Krzysztof Pniaczek
Michał Karp
Jacek Tabor
CLL
582
0
0
18 Mar 2025
Trading-off Accuracy and Communication Cost in Federated Learning
Trading-off Accuracy and Communication Cost in Federated LearningAdaptive Agents and Multi-Agent Systems (AAMAS), 2025
Mattia Jacopo Villani
Emanuele Natale
Frederik Mallmann-Trenn
FedML
296
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18 Mar 2025
Enhanced Soups for Graph Neural NetworksIEEE International Symposium on Parallel & Distributed Processing, Workshops and Phd Forum (IPDPS), 2025
Joseph Zuber
Aishwarya Sarkar
Joseph Jennings
Ali Jannesari
281
1
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Are formal and functional linguistic mechanisms dissociated in language models?
Are formal and functional linguistic mechanisms dissociated in language models?
Michael Hanna
Sandro Pezzelle
Yonatan Belinkov
523
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14 Mar 2025
Explainable Bayesian deep learning through input-skip Latent Binary Bayesian Neural Networks
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Lars Skaaret-Lund
Solve Sæbø
A. Hubin
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234
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PRISM: Privacy-Preserving Improved Stochastic Masking for Federated Generative Models
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Kyeongkook Seo
Dong-Jun Han
Jaejun Yoo
496
2
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11 Mar 2025
ResMoE: Space-efficient Compression of Mixture of Experts LLMs via Residual RestorationKnowledge Discovery and Data Mining (KDD), 2025
Mengting Ai
Tianxin Wei
Yifan Chen
Zhichen Zeng
Ritchie Zhao
G. Varatkar
B. Rouhani
Xianfeng Tang
Hanghang Tong
Jingrui He
MoE
271
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0
10 Mar 2025
PRO-VPT: Distribution-Adaptive Visual Prompt Tuning via Prompt Relocation
PRO-VPT: Distribution-Adaptive Visual Prompt Tuning via Prompt Relocation
Chikai Shang
Mengke Li
Yiqun Zhang
Daming Gao
Jinlin Wu
Fangqing Gu
Yang Lu
Yiu-ming Cheung
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351
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0
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How can representation dimension dominate structurally pruned LLMs?
Mingxue Xu
Lisa Alazraki
Danilo Mandic
268
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Wanda++: Pruning Large Language Models via Regional Gradients
Wanda++: Pruning Large Language Models via Regional GradientsAnnual Meeting of the Association for Computational Linguistics (ACL), 2025
Yifan Yang
Kai Zhen
Bhavana Ganesh
Aram Galstyan
Goeric Huybrechts
...
S. Bodapati
Nathan Susanj
Zheng Zhang
Jack FitzGerald
Abhishek Kumar
569
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0
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GaussianVideo: Efficient Video Representation and Compression by Gaussian Splatting
Inseo Lee
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Joonseok Lee
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225
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Keeping Yourself is Important in Downstream Tuning Multimodal Large Language Model
Wenke Huang
Jian Liang
Xianda Guo
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Bin Yang
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Di Lin
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350
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A Theory of Initialisation's Impact on SpecialisationInternational Conference on Learning Representations (ICLR), 2025
Devon Jarvis
Sebastian Lee
Clémentine Dominé
Andrew M. Saxe
Stefano Sarao Mannelli
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296
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0
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Eau De $Q$-Network: Adaptive Distillation of Neural Networks in Deep Reinforcement Learning
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Théo Vincent
Tim Lukas Faust
Yogesh Tripathi
Jan Peters
Carlo DÉramo
264
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Everything, Everywhere, All at Once: Is Mechanistic Interpretability Identifiable?
Everything, Everywhere, All at Once: Is Mechanistic Interpretability Identifiable?International Conference on Learning Representations (ICLR), 2025
Maxime Méloux
Silviu Maniu
François Portet
Maxime Peyrard
284
11
0
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Position: Solve Layerwise Linear Models First to Understand Neural Dynamical Phenomena (Neural Collapse, Emergence, Lazy/Rich Regime, and Grokking)
Position: Solve Layerwise Linear Models First to Understand Neural Dynamical Phenomena (Neural Collapse, Emergence, Lazy/Rich Regime, and Grokking)
Yoonsoo Nam
Seok Hyeong Lee
Clementine Domine
Yea Chan Park
Charles London
Wonyl Choi
Niclas Goring
Seungjai Lee
AI4CE
542
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Sparse Brains are Also Adaptive Brains: Cognitive-Load-Aware Dynamic Activation for LLMs
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Yiheng Yang
Yujie Wang
Chi Ma
Lei Yu
Emmanuele Chersoni
Chu-Ren Huang
310
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Tamer Ghattas
Michael Hassid
Roy Schwartz
250
4
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26 Feb 2025
CABS: Conflict-Aware and Balanced Sparsification for Enhancing Model Merging
Zongzhen Yang
Binhang Qi
Hailong Sun
Wenrui Long
Ruobing Zhao
Yantao Du
MoMe
277
4
0
26 Feb 2025
Constraining Sequential Model Editing with Editing Anchor CompressionNorth American Chapter of the Association for Computational Linguistics (NAACL), 2025
Hao-Xiang Xu
Jun-Yu Ma
Zhen-Hua Ling
Ningyu Zhang
Jia-Chen Gu
KELM
264
1
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25 Feb 2025
Personalized Federated Learning for Egocentric Video Gaze Estimation with Comprehensive Parameter Frezzing
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Yuhu Feng
Keisuke Maeda
Takahiro Ogawa
Miki Haseyama
FedMLEgoV
249
0
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Geometric Properties and Graph-Based Optimization of Neural Networks: Addressing Non-Linearity, Dimensionality, and Scalability
Michael Wienczkowski
Addisu Desta
Paschal Ugochukwu
AI4CEGNN
145
0
0
24 Feb 2025
Systematic Weight Evaluation for Pruning Large Language Models: Enhancing Performance and Sustainability
Systematic Weight Evaluation for Pruning Large Language Models: Enhancing Performance and Sustainability
Ashhadul Islam
S. Belhaouari
Amine Bermak
232
0
0
24 Feb 2025
Spectral Theory for Edge Pruning in Asynchronous Recurrent Graph Neural Networks
Spectral Theory for Edge Pruning in Asynchronous Recurrent Graph Neural Networks
Nicolas Bessone
133
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0
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Automatic Joint Structured Pruning and Quantization for Efficient Neural Network Training and Compression
Automatic Joint Structured Pruning and Quantization for Efficient Neural Network Training and CompressionComputer Vision and Pattern Recognition (CVPR), 2025
Xiaoyi Qu
David Aponte
Colby R. Banbury
Daniel P. Robinson
Tianyu Ding
K. Koishida
Ilya Zharkov
Tianyi Chen
MQ
319
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0
23 Feb 2025
Keep what you need : extracting efficient subnetworks from large audio representation models
Keep what you need : extracting efficient subnetworks from large audio representation modelsIEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), 2025
David Genova
P. Esling
Tom Hurlin
208
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Signal Collapse in One-Shot Pruning: When Sparse Models Fail to Distinguish Neural Representations
Signal Collapse in One-Shot Pruning: When Sparse Models Fail to Distinguish Neural Representations
Dhananjay Saikumar
Blesson Varghese
209
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0
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FitLight: Federated Imitation Learning for Plug-and-Play Autonomous Traffic Signal Control
FitLight: Federated Imitation Learning for Plug-and-Play Autonomous Traffic Signal Control
Yutong Ye
Yingbo Zhou
Zhusen Liu
Xiao Du
Hao Zhou
Xiang Lian
Xiao He
182
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0
17 Feb 2025
Fishing For Cheap And Efficient Pruners At Initialization
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Ivo Gollini Navarrete
Nicolas Mauricio Cuadrado
Jose Renato Restom
Martin Takáč
Samuel Horvath
224
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Forget the Data and Fine-Tuning! Just Fold the Network to Compress
Forget the Data and Fine-Tuning! Just Fold the Network to CompressInternational Conference on Learning Representations (ICLR), 2025
Dong Wang
Haris Šikić
Lothar Thiele
O. Saukh
334
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Graph Neural Networks at a Fraction
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Rucha Bhalchandra Joshi
Sagar Prakash Barad
Nidhi Tiwari
Subhankar Mishra
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362
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The impact of allocation strategies in subset learning on the expressive power of neural networksInternational Conference on Learning Representations (ICLR), 2025
Ofir Schlisselberg
Ran Darshan
308
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Contrastive Representation Distillation via Multi-Scale Feature Decoupling
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Tieyuan Chen
372
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Training-Free Restoration of Pruned Neural Networks
Training-Free Restoration of Pruned Neural Networks
Keonho Lee
Minsoo Kim
Dong-Wan Choi
319
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Studying Cross-cluster Modularity in Neural Networks
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Satvik Golechha
Maheep Chaudhary
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Nandi Schoots
347
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Deep Weight Factorization: Sparse Learning Through the Lens of Artificial Symmetries
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T. Weber
B. Bischl
David Rügamer
830
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Accelerating Linear Recurrent Neural Networks for the Edge with Unstructured Sparsity
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Alessandro Pierro
Steven Abreu
Jonathan Timcheck
Philipp Stratmann
Andreas Wild
S. Shrestha
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Language Bias in Self-Supervised Learning For Automatic Speech Recognition
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Edward Storey
Naomi Harte
Peter Bell
156
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Symmetric Pruning of Large Language Models
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Kai Yi
Peter Richtárik
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320
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Algebra Unveils Deep Learning -- An Invitation to Neuroalgebraic Geometry
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Vahid Shahverdi
Stefano Mereta
Matthew Trager
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344
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Information Consistent Pruning: How to Efficiently Search for Sparse Networks?
Soheil Gharatappeh
Salimeh Yasaei Sekeh
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Meta-Sparsity: Learning Optimal Sparse Structures in Multi-task Networks through Meta-learning
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Richa Upadhyay
Ronald Phlypo
Rajkumar Saini
Marcus Liwicki
296
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Playing the Lottery With Concave Regularizers for Sparse Trainable Neural Networks
Playing the Lottery With Concave Regularizers for Sparse Trainable Neural NetworksIEEE Transactions on Neural Networks and Learning Systems (TNNLS), 2024
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Sophie M. Fosson
Andrea Migliorati
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278
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DynST: Dynamic Sparse Training for Resource-Constrained Spatio-Temporal Forecasting
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Haomin Wen
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430
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Pruning for Sparse Diffusion Models based on Gradient Flow
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128
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