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TT-MPD: Test Time Model Pruning and Distillation

TT-MPD: Test Time Model Pruning and Distillation

10 December 2024
Haihang Wu
Wei Wang
T. Malepathirana
Sachith Seneviratne
D. Oetomo
Saman K. Halgamuge
ArXiv (abs)PDFHTML

Papers citing "TT-MPD: Test Time Model Pruning and Distillation"

18 / 18 papers shown
Title
HomoDistil: Homotopic Task-Agnostic Distillation of Pre-trained
  Transformers
HomoDistil: Homotopic Task-Agnostic Distillation of Pre-trained Transformers
Chen Liang
Haoming Jiang
Zheng Li
Xianfeng Tang
Bin Yin
Tuo Zhao
VLM
115
25
0
19 Feb 2023
Efficient Test-Time Model Adaptation without Forgetting
Efficient Test-Time Model Adaptation without Forgetting
Shuaicheng Niu
Jiaxiang Wu
Yifan Zhang
Yaofo Chen
S. Zheng
P. Zhao
Mingkui Tan
OODVLMTTA
91
350
0
06 Apr 2022
Compressing Models with Few Samples: Mimicking then Replacing
Compressing Models with Few Samples: Mimicking then Replacing
Huanyu Wang
Junjie Liu
Xin Ma
Yang Yong
Z. Chai
Jianxin Wu
VLMOffRL
53
13
0
07 Jan 2022
Group Fisher Pruning for Practical Network Compression
Group Fisher Pruning for Practical Network Compression
Liyang Liu
Shilong Zhang
Zhanghui Kuang
Aojun Zhou
Jingliang Xue
Xinjiang Wang
Yimin Chen
Wenming Yang
Q. Liao
Wayne Zhang
88
149
0
02 Aug 2021
Knowledge distillation: A good teacher is patient and consistent
Knowledge distillation: A good teacher is patient and consistent
Lucas Beyer
Xiaohua Zhai
Amelie Royer
L. Markeeva
Rohan Anil
Alexander Kolesnikov
VLM
109
299
0
09 Jun 2021
Neuron Merging: Compensating for Pruned Neurons
Neuron Merging: Compensating for Pruned Neurons
Woojeong Kim
Suhyun Kim
Mincheol Park
Geonseok Jeon
70
32
0
25 Oct 2020
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
684
41,563
0
22 Oct 2020
The Many Faces of Robustness: A Critical Analysis of Out-of-Distribution
  Generalization
The Many Faces of Robustness: A Critical Analysis of Out-of-Distribution Generalization
Dan Hendrycks
Steven Basart
Norman Mu
Saurav Kadavath
Frank Wang
...
Samyak Parajuli
Mike Guo
Basel Alomair
Jacob Steinhardt
Justin Gilmer
OOD
363
1,757
0
29 Jun 2020
DynaBERT: Dynamic BERT with Adaptive Width and Depth
DynaBERT: Dynamic BERT with Adaptive Width and Depth
Lu Hou
Zhiqi Huang
Lifeng Shang
Xin Jiang
Xiao Chen
Qun Liu
MQ
84
322
0
08 Apr 2020
Neural Network Pruning with Residual-Connections and Limited-Data
Neural Network Pruning with Residual-Connections and Limited-Data
Jian-Hao Luo
Jianxin Wu
68
114
0
19 Nov 2019
DistilBERT, a distilled version of BERT: smaller, faster, cheaper and
  lighter
DistilBERT, a distilled version of BERT: smaller, faster, cheaper and lighter
Victor Sanh
Lysandre Debut
Julien Chaumond
Thomas Wolf
267
7,554
0
02 Oct 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
196
3,458
0
28 Mar 2019
Filter Pruning via Geometric Median for Deep Convolutional Neural
  Networks Acceleration
Filter Pruning via Geometric Median for Deep Convolutional Neural Networks Acceleration
Yang He
Ping Liu
Ziwei Wang
Zhilan Hu
Yi Yang
AAML3DPC
98
1,050
0
01 Nov 2018
MobileNetV2: Inverted Residuals and Linear Bottlenecks
MobileNetV2: Inverted Residuals and Linear Bottlenecks
Mark Sandler
Andrew G. Howard
Menglong Zhu
A. Zhmoginov
Liang-Chieh Chen
220
19,353
0
13 Jan 2018
Residual Connections Encourage Iterative Inference
Residual Connections Encourage Iterative Inference
Stanislaw Jastrzebski
Devansh Arpit
Nicolas Ballas
Vikas Verma
Tong Che
Yoshua Bengio
74
155
0
13 Oct 2017
ThiNet: A Filter Level Pruning Method for Deep Neural Network
  Compression
ThiNet: A Filter Level Pruning Method for Deep Neural Network Compression
Jian-Hao Luo
Jianxin Wu
Weiyao Lin
58
1,761
0
20 Jul 2017
Deep Residual Learning for Image Recognition
Deep Residual Learning for Image Recognition
Kaiming He
Xinming Zhang
Shaoqing Ren
Jian Sun
MedIm
2.3K
194,641
0
10 Dec 2015
Deep Compression: Compressing Deep Neural Networks with Pruning, Trained
  Quantization and Huffman Coding
Deep Compression: Compressing Deep Neural Networks with Pruning, Trained Quantization and Huffman Coding
Song Han
Huizi Mao
W. Dally
3DGS
263
8,864
0
01 Oct 2015
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