Effective Compression of Language Models by Combining Pruning and Knowledge Distillation-Reference-Cited by-同舟云学术

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Effective Compression of Language Models by Combining Pruning and Knowledge Distillation

Published:2024-07-02 Issue: Volume:30 Page:429-438
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Container-title:2024 IEEE 48th Annual Computers, Software, and Applications Conference (COMPSAC)
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Author:

Chiu Chi-Yu¹,Hong Ding-Yong²,Liu Pangfeng³,Wu Jan-Jan²

Affiliation:

1. Graduate Institute of Networking and Multimedia, National Taiwan University,Taipei,Taiwan

2. Institute of Information Science, Academia Sinica,Taipei,Taiwan

3. Graduate Institute of Networking and Multimedia, National Taiwan University,Department of Computer Science and Information Engineering,Taipei,Taiwan

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx8/10633276/10633246/10633390.pdf?arnumber=10633390

Reference28 articles.

1. Attention is all you need;Vaswani,2017

2. BERT: Pre-training of deep bidirectional transformers for language understanding;Devlin

3. Distilling the Knowledge in a Neural Network;Hinton;NIPS 2014 Deep Learning Workshop,2015

4. Compressing deep convolutional networks using vector quantization;Gong;CoRR,2014

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