How Well Do Sparse Imagenet Models Transfer?

How Well Do Sparse Imagenet Models Transfer?

26 November 2021

Eugenia Iofinova

Alexandra Peste

Dan Alistarh

Papers citing "How Well Do Sparse Imagenet Models Transfer?"

15 / 15 papers shown

Title
Token Coordinated Prompt Attention is Needed for Visual Prompting Zichen Liu Xu Zou Gang Hua Jiahuan Zhou 34 0 0 05 May 2025
Revisiting Prefix-tuning: Statistical Benefits of Reparameterization among Prompts Minh Le Chau Nguyen Huy Nguyen Quyen Tran Trung Le Nhat Ho 32 4 0 03 Oct 2024
Which Backbone to Use: A Resource-efficient Domain Specific Comparison for Computer Vision Pranav Jeevan Amit Sethi VLM 31 4 0 09 Jun 2024
Multilingual Brain Surgeon: Large Language Models Can be Compressed Leaving No Language Behind Hongchuan Zeng Hongshen Xu Lu Chen Kai Yu 47 5 0 06 Apr 2024
Uncovering the Hidden Cost of Model Compression Diganta Misra Muawiz Chaudhary Agam Goyal Bharat Runwal Pin-Yu Chen VLM 24 0 0 29 Aug 2023
Robust Tickets Can Transfer Better: Drawing More Transferable Subnetworks in Transfer Learning Y. Fu Ye Yuan Shang Wu Jiayi Yuan Yingyan Lin OOD 50 3 0 24 Apr 2023
oBERTa: Improving Sparse Transfer Learning via improved initialization, distillation, and pruning regimes Daniel Fernando Campos Alexandre Marques Mark Kurtz Chengxiang Zhai VLM AAML 11 2 0 30 Mar 2023
Sparse-IFT: Sparse Iso-FLOP Transformations for Maximizing Training Efficiency Vithursan Thangarasa Shreyas Saxena Abhay Gupta Sean Lie 21 3 0 21 Mar 2023
GPTQ: Accurate Post-Training Quantization for Generative Pre-trained Transformers Elias Frantar Saleh Ashkboos Torsten Hoefler Dan Alistarh MQ 14 882 0 31 Oct 2022
Efficient Methods for Natural Language Processing: A Survey Marcos Vinícius Treviso Ji-Ung Lee Tianchu Ji Betty van Aken Qingqing Cao ... Emma Strubell Niranjan Balasubramanian Leon Derczynski Iryna Gurevych Roy Schwartz 28 109 0 31 Aug 2022
Federated Progressive Sparsification (Purge, Merge, Tune)+ Dimitris Stripelis Umang Gupta Greg Ver Steeg J. Ambite FedML 13 9 0 26 Apr 2022
Sparsity in Deep Learning: Pruning and growth for efficient inference and training in neural networks Torsten Hoefler Dan Alistarh Tal Ben-Nun Nikoli Dryden Alexandra Peste MQ 139 684 0 31 Jan 2021
The Lottery Ticket Hypothesis for Object Recognition Sharath Girish Shishira R. Maiya Kamal Gupta Hao Chen L. Davis Abhinav Shrivastava 75 60 0 08 Dec 2020
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
MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications Andrew G. Howard Menglong Zhu Bo Chen Dmitry Kalenichenko Weijun Wang Tobias Weyand M. Andreetto Hartwig Adam 3DH 948 20,549 0 17 Apr 2017