Vision Transformer Compression with Structured Pruning and Low Rank Approximation

25 March 2022

Papers citing "Vision Transformer Compression with Structured Pruning and Low Rank Approximation"

7 / 7 papers shown

Title
Research on Personalized Compression Algorithm for Pre-trained Models Based on Homomorphic Entropy Increase Yicong Li Xing Guo Haohua Du 35 0 0 16 Aug 2024
Memory-Efficient Vision Transformers: An Activation-Aware Mixed-Rank Compression Strategy Seyedarmin Azizi M. Nazemi Massoud Pedram ViT MQ 38 2 0 08 Feb 2024
Compressing Vision Transformers for Low-Resource Visual Learning Eric Youn J. SaiMitheran Sanjana Prabhu Siyuan Chen ViT 27 2 0 05 Sep 2023
Low Rank Optimization for Efficient Deep Learning: Making A Balance between Compact Architecture and Fast Training Xinwei Ou Zhangxin Chen Ce Zhu Yipeng Liu 31 4 0 22 Mar 2023
Zero-Shot Text-to-Image Generation Aditya A. Ramesh Mikhail Pavlov Gabriel Goh Scott Gray Chelsea Voss Alec Radford Mark Chen Ilya Sutskever VLM 255 4,781 0 24 Feb 2021
What is the State of Neural Network Pruning? Davis W. Blalock Jose Javier Gonzalez Ortiz Jonathan Frankle John Guttag 191 1,027 0 06 Mar 2020
Scaling Laws for Neural Language Models Jared Kaplan Sam McCandlish T. Henighan Tom B. Brown B. Chess R. Child Scott Gray Alec Radford Jeff Wu Dario Amodei 243 4,469 0 23 Jan 2020