How to Prune Your Language Model: Recovering Accuracy on the "Sparsity
May Cry'' Benchmark

How to Prune Your Language Model: Recovering Accuracy on the "Sparsity May Cry'' Benchmark

21 December 2023

Torsten Hoefler

Dan Alistarh

Papers citing "How to Prune Your Language Model: Recovering Accuracy on the "Sparsity May Cry'' Benchmark"

4 / 4 papers shown

Title
Navigating Extremes: Dynamic Sparsity in Large Output Spaces Nasib Ullah Erik Schultheis Mike Lasby Yani Andrew Ioannou Rohit Babbar 33 0 0 05 Nov 2024
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 148 376 0 23 Jul 2020
GLUE: A Multi-Task Benchmark and Analysis Platform for Natural Language Understanding Alex Jinpeng Wang Amanpreet Singh Julian Michael Felix Hill Omer Levy Samuel R. Bowman ELM 294 6,950 0 20 Apr 2018