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KDLSQ-BERT: A Quantized Bert Combining Knowledge Distillation with
  Learned Step Size Quantization

KDLSQ-BERT: A Quantized Bert Combining Knowledge Distillation with Learned Step Size Quantization

15 January 2021
Jing Jin
Cai Liang
Tiancheng Wu
Li Zou
Zhiliang Gan
    MQ
ArXiv (abs)PDFHTML

Papers citing "KDLSQ-BERT: A Quantized Bert Combining Knowledge Distillation with Learned Step Size Quantization"

36 / 36 papers shown
Title
On the Impact of White-box Deployment Strategies for Edge AI on Latency and Model Performance
On the Impact of White-box Deployment Strategies for Edge AI on Latency and Model Performance
Jaskirat Singh
Bram Adams
Ahmed E. Hassan
VLM
91
0
0
01 Nov 2024
TernaryBERT: Distillation-aware Ultra-low Bit BERT
TernaryBERT: Distillation-aware Ultra-low Bit BERT
Wei Zhang
Lu Hou
Yichun Yin
Lifeng Shang
Xiao Chen
Xin Jiang
Qun Liu
MQ
93
211
0
27 Sep 2020
GOBO: Quantizing Attention-Based NLP Models for Low Latency and Energy
  Efficient Inference
GOBO: Quantizing Attention-Based NLP Models for Low Latency and Energy Efficient Inference
Ali Hadi Zadeh
Isak Edo
Omar Mohamed Awad
Andreas Moshovos
MQ
65
188
0
08 May 2020
Training with Quantization Noise for Extreme Model Compression
Training with Quantization Noise for Extreme Model Compression
Angela Fan
Pierre Stock
Benjamin Graham
Edouard Grave
Remi Gribonval
Hervé Jégou
Armand Joulin
MQ
93
245
0
15 Apr 2020
LadaBERT: Lightweight Adaptation of BERT through Hybrid Model
  Compression
LadaBERT: Lightweight Adaptation of BERT through Hybrid Model Compression
Yihuan Mao
Yujing Wang
Chufan Wu
Chen Zhang
Yang-Feng Wang
Yaming Yang
Quanlu Zhang
Yunhai Tong
Jing Bai
49
74
0
08 Apr 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
79
322
0
08 Apr 2020
MiniLM: Deep Self-Attention Distillation for Task-Agnostic Compression
  of Pre-Trained Transformers
MiniLM: Deep Self-Attention Distillation for Task-Agnostic Compression of Pre-Trained Transformers
Wenhui Wang
Furu Wei
Li Dong
Hangbo Bao
Nan Yang
Ming Zhou
VLM
156
1,278
0
25 Feb 2020
QKD: Quantization-aware Knowledge Distillation
QKD: Quantization-aware Knowledge Distillation
Jangho Kim
Yash Bhalgat
Jinwon Lee
Chirag I. Patel
Nojun Kwak
MQ
90
66
0
28 Nov 2019
Structured Pruning of a BERT-based Question Answering Model
Structured Pruning of a BERT-based Question Answering Model
J. Scott McCarley
Rishav Chakravarti
Avirup Sil
54
53
0
14 Oct 2019
Q8BERT: Quantized 8Bit BERT
Q8BERT: Quantized 8Bit BERT
Ofir Zafrir
Guy Boudoukh
Peter Izsak
Moshe Wasserblat
MQ
83
505
0
14 Oct 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
234
7,520
0
02 Oct 2019
ALBERT: A Lite BERT for Self-supervised Learning of Language
  Representations
ALBERT: A Lite BERT for Self-supervised Learning of Language Representations
Zhenzhong Lan
Mingda Chen
Sebastian Goodman
Kevin Gimpel
Piyush Sharma
Radu Soricut
SSLAIMat
371
6,463
0
26 Sep 2019
Reducing Transformer Depth on Demand with Structured Dropout
Reducing Transformer Depth on Demand with Structured Dropout
Angela Fan
Edouard Grave
Armand Joulin
120
595
0
25 Sep 2019
TinyBERT: Distilling BERT for Natural Language Understanding
TinyBERT: Distilling BERT for Natural Language Understanding
Xiaoqi Jiao
Yichun Yin
Lifeng Shang
Xin Jiang
Xiao Chen
Linlin Li
F. Wang
Qun Liu
VLM
109
1,860
0
23 Sep 2019
Patient Knowledge Distillation for BERT Model Compression
Patient Knowledge Distillation for BERT Model Compression
S. Sun
Yu Cheng
Zhe Gan
Jingjing Liu
134
843
0
25 Aug 2019
RoBERTa: A Robustly Optimized BERT Pretraining Approach
RoBERTa: A Robustly Optimized BERT Pretraining Approach
Yinhan Liu
Myle Ott
Naman Goyal
Jingfei Du
Mandar Joshi
Danqi Chen
Omer Levy
M. Lewis
Luke Zettlemoyer
Veselin Stoyanov
AIMat
668
24,528
0
26 Jul 2019
And the Bit Goes Down: Revisiting the Quantization of Neural Networks
And the Bit Goes Down: Revisiting the Quantization of Neural Networks
Pierre Stock
Armand Joulin
Rémi Gribonval
Benjamin Graham
Hervé Jégou
MQ
82
149
0
12 Jul 2019
A Tensorized Transformer for Language Modeling
A Tensorized Transformer for Language Modeling
Xindian Ma
Peng Zhang
Shuai Zhang
Nan Duan
Yuexian Hou
D. Song
M. Zhou
63
167
0
24 Jun 2019
XLNet: Generalized Autoregressive Pretraining for Language Understanding
XLNet: Generalized Autoregressive Pretraining for Language Understanding
Zhilin Yang
Zihang Dai
Yiming Yang
J. Carbonell
Ruslan Salakhutdinov
Quoc V. Le
AI4CE
232
8,444
0
19 Jun 2019
What Does BERT Look At? An Analysis of BERT's Attention
What Does BERT Look At? An Analysis of BERT's Attention
Kevin Clark
Urvashi Khandelwal
Omer Levy
Christopher D. Manning
MILM
218
1,601
0
11 Jun 2019
Are Sixteen Heads Really Better than One?
Are Sixteen Heads Really Better than One?
Paul Michel
Omer Levy
Graham Neubig
MoE
103
1,062
0
25 May 2019
Analyzing Multi-Head Self-Attention: Specialized Heads Do the Heavy
  Lifting, the Rest Can Be Pruned
Analyzing Multi-Head Self-Attention: Specialized Heads Do the Heavy Lifting, the Rest Can Be Pruned
Elena Voita
David Talbot
F. Moiseev
Rico Sennrich
Ivan Titov
114
1,146
0
23 May 2019
Trained Quantization Thresholds for Accurate and Efficient Fixed-Point
  Inference of Deep Neural Networks
Trained Quantization Thresholds for Accurate and Efficient Fixed-Point Inference of Deep Neural Networks
Sambhav R. Jain
Albert Gural
Michael Wu
Chris Dick
MQ
77
152
0
19 Mar 2019
Learned Step Size Quantization
Learned Step Size Quantization
S. K. Esser
J. McKinstry
Deepika Bablani
R. Appuswamy
D. Modha
MQ
75
809
0
21 Feb 2019
BERT: Pre-training of Deep Bidirectional Transformers for Language
  Understanding
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
Jacob Devlin
Ming-Wei Chang
Kenton Lee
Kristina Toutanova
VLMSSLSSeg
1.8K
95,114
0
11 Oct 2018
Attention-Guided Answer Distillation for Machine Reading Comprehension
Attention-Guided Answer Distillation for Machine Reading Comprehension
Minghao Hu
Yuxing Peng
Furu Wei
Zhen Huang
Dongsheng Li
Nan Yang
M. Zhou
FaML
60
75
0
23 Aug 2018
Quantizing deep convolutional networks for efficient inference: A
  whitepaper
Quantizing deep convolutional networks for efficient inference: A whitepaper
Raghuraman Krishnamoorthi
MQ
141
1,019
0
21 Jun 2018
GLUE: A Multi-Task Benchmark and Analysis Platform for Natural Language
  Understanding
GLUE: A Multi-Task Benchmark and Analysis Platform for Natural Language Understanding
Alex Jinpeng Wang
Amanpreet Singh
Julian Michael
Felix Hill
Omer Levy
Samuel R. Bowman
ELM
1.1K
7,182
0
20 Apr 2018
Model compression via distillation and quantization
Model compression via distillation and quantization
A. Polino
Razvan Pascanu
Dan Alistarh
MQ
83
731
0
15 Feb 2018
Quantization and Training of Neural Networks for Efficient
  Integer-Arithmetic-Only Inference
Quantization and Training of Neural Networks for Efficient Integer-Arithmetic-Only Inference
Benoit Jacob
S. Kligys
Bo Chen
Menglong Zhu
Matthew Tang
Andrew G. Howard
Hartwig Adam
Dmitry Kalenichenko
MQ
156
3,138
0
15 Dec 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
728
132,199
0
12 Jun 2017
Sequence-Level Knowledge Distillation
Sequence-Level Knowledge Distillation
Yoon Kim
Alexander M. Rush
122
1,120
0
25 Jun 2016
SQuAD: 100,000+ Questions for Machine Comprehension of Text
SQuAD: 100,000+ Questions for Machine Comprehension of Text
Pranav Rajpurkar
Jian Zhang
Konstantin Lopyrev
Percy Liang
RALM
296
8,160
0
16 Jun 2016
Distilling the Knowledge in a Neural Network
Distilling the Knowledge in a Neural Network
Geoffrey E. Hinton
Oriol Vinyals
J. Dean
FedML
362
19,723
0
09 Mar 2015
FitNets: Hints for Thin Deep Nets
FitNets: Hints for Thin Deep Nets
Adriana Romero
Nicolas Ballas
Samira Ebrahimi Kahou
Antoine Chassang
C. Gatta
Yoshua Bengio
FedML
308
3,893
0
19 Dec 2014
Estimating or Propagating Gradients Through Stochastic Neurons for
  Conditional Computation
Estimating or Propagating Gradients Through Stochastic Neurons for Conditional Computation
Yoshua Bengio
Nicholas Léonard
Aaron Courville
384
3,151
0
15 Aug 2013
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