Compressing LLMs: The Truth is Rarely Pure and Never Simple

Compressing LLMs: The Truth is Rarely Pure and Never Simple

2 October 2023

Xianzhi Du

Papers citing "Compressing LLMs: The Truth is Rarely Pure and Never Simple"

10 / 10 papers shown

Title
Stability in Single-Peaked Strategic Resource Selection Games Henri Zeiler 9 0 0 09 May 2025
Radio: Rate-Distortion Optimization for Large Language Model Compression Sean I. Young MQ 12 0 0 05 May 2025
Efficient Shapley Value-based Non-Uniform Pruning of Large Language Models Chuan Sun Han Yu Lizhen Cui 18 0 0 03 May 2025
iServe: An Intent-based Serving System for LLMs Dimitrios Liakopoulos Tianrui Hu Prasoon Sinha N. Yadwadkar VLM 44 0 0 08 Jan 2025
Navigating Extremes: Dynamic Sparsity in Large Output Spaces Nasib Ullah Erik Schultheis Mike Lasby Yani Andrew Ioannou Rohit Babbar 21 0 0 05 Nov 2024
WAGLE: Strategic Weight Attribution for Effective and Modular Unlearning in Large Language Models Jinghan Jia Jiancheng Liu Yihua Zhang Parikshit Ram Nathalie Baracaldo Sijia Liu MU 28 2 0 23 Oct 2024
Instant Soup: Cheap Pruning Ensembles in A Single Pass Can Draw Lottery Tickets from Large Models A. Jaiswal Shiwei Liu Tianlong Chen Ying Ding Zhangyang Wang VLM 29 22 0 18 Jun 2023
FlexGen: High-Throughput Generative Inference of Large Language Models with a Single GPU Ying Sheng Lianmin Zheng Binhang Yuan Zhuohan Li Max Ryabinin ... Joseph E. Gonzalez Percy Liang Christopher Ré Ion Stoica Ce Zhang 135 208 0 13 Mar 2023
I-BERT: Integer-only BERT Quantization Sehoon Kim A. Gholami Z. Yao Michael W. Mahoney Kurt Keutzer MQ 75 332 0 05 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 139 375 0 23 Jul 2020