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Rethinking Pruning for Vision-Language Models: Strategies for Effective
  Sparsity and Performance Restoration

Rethinking Pruning for Vision-Language Models: Strategies for Effective Sparsity and Performance Restoration

3 April 2024
Shwai He
Ang Li
Tianlong Chen
    VLM
ArXivPDFHTML

Papers citing "Rethinking Pruning for Vision-Language Models: Strategies for Effective Sparsity and Performance Restoration"

4 / 4 papers shown
Title
Everybody Prune Now: Structured Pruning of LLMs with only Forward Passes
Everybody Prune Now: Structured Pruning of LLMs with only Forward Passes
Lucio Dery
Steven Kolawole
Jean-Francois Kagey
Virginia Smith
Graham Neubig
Ameet Talwalkar
39
27
0
08 Feb 2024
BLIP: Bootstrapping Language-Image Pre-training for Unified
  Vision-Language Understanding and Generation
BLIP: Bootstrapping Language-Image Pre-training for Unified Vision-Language Understanding and Generation
Junnan Li
Dongxu Li
Caiming Xiong
S. Hoi
MLLM
BDL
VLM
CLIP
388
4,010
0
28 Jan 2022
An Empirical Study of GPT-3 for Few-Shot Knowledge-Based VQA
An Empirical Study of GPT-3 for Few-Shot Knowledge-Based VQA
Zhengyuan Yang
Zhe Gan
Jianfeng Wang
Xiaowei Hu
Yumao Lu
Zicheng Liu
Lijuan Wang
169
401
0
10 Sep 2021
The Lottery Ticket Hypothesis for Pre-trained BERT Networks
The Lottery Ticket Hypothesis for Pre-trained BERT Networks
Tianlong Chen
Jonathan Frankle
Shiyu Chang
Sijia Liu
Yang Zhang
Zhangyang Wang
Michael Carbin
148
345
0
23 Jul 2020
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