What Makes Quantization for Large Language Models Hard? An Empirical
Study from the Lens of Perturbation

What Makes Quantization for Large Language Models Hard? An Empirical Study from the Lens of Perturbation

11 March 2024

Dongyan Zhao

Rui Yan

Papers citing "What Makes Quantization for Large Language Models Hard? An Empirical Study from the Lens of Perturbation"

7 / 7 papers shown

Title
Efficient Fine-Tuning of Quantized Models via Adaptive Rank and Bitwidth Changhai Zhou Yuhua Zhou Qian Qiao Weizhong Zhang Cheng Jin MQ 27 0 0 02 May 2025
How Does Quantization Affect Multilingual LLMs? Kelly Marchisio Saurabh Dash Hongyu Chen Dennis Aumiller A. Ustun Sara Hooker Sebastian Ruder MQ 52 8 0 03 Jul 2024
Pruning via Merging: Compressing LLMs via Manifold Alignment Based Layer Merging Deyuan Liu Zhanyue Qin Hairu Wang Zhao Yang Zecheng Wang ... Zhao Lv Zhiying Tu Dianhui Chu Bo Li Dianbo Sui 22 2 0 24 Jun 2024
Perturbation-Restrained Sequential Model Editing Junjie Ma Hong Wang Haoyang Xu Zhen-Hua Ling Jia-Chen Gu KELM 59 8 0 27 May 2024
ZeroQuant-V2: Exploring Post-training Quantization in LLMs from Comprehensive Study to Low Rank Compensation Z. Yao Xiaoxia Wu Cheng-rong Li Stephen Youn Yuxiong He MQ 63 57 0 15 Mar 2023
I-BERT: Integer-only BERT Quantization Sehoon Kim A. Gholami Z. Yao Michael W. Mahoney Kurt Keutzer MQ 105 341 0 05 Jan 2021
Q-BERT: Hessian Based Ultra Low Precision Quantization of BERT Sheng Shen Zhen Dong Jiayu Ye Linjian Ma Z. Yao A. Gholami Michael W. Mahoney Kurt Keutzer MQ 233 576 0 12 Sep 2019