GMP*: Well-Tuned Gradual Magnitude Pruning Can Outperform Most
BERT-Pruning Methods

GMP*: Well-Tuned Gradual Magnitude Pruning Can Outperform Most BERT-Pruning Methods

12 October 2022

Dan Alistarh

Papers citing "GMP*: Well-Tuned Gradual Magnitude Pruning Can Outperform Most BERT-Pruning Methods"

4 / 4 papers shown

Title
Beyond Perplexity: Multi-dimensional Safety Evaluation of LLM Compression Zhichao Xu Ashim Gupta Tao Li Oliver Bentham Vivek Srikumar 40 8 0 06 Jul 2024
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
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 Pre-trained BERT Networks Tianlong Chen Jonathan Frankle Shiyu Chang Sijia Liu Yang Zhang Zhangyang Wang Michael Carbin 148 345 0 23 Jul 2020