QuantEase: Optimization-based Quantization for Language Models

QuantEase: Optimization-based Quantization for Language Models

5 September 2023

Papers citing "QuantEase: Optimization-based Quantization for Language Models"

10 / 10 papers shown

Title
Semantic Retention and Extreme Compression in LLMs: Can We Have Both? Stanislas Laborde Martin Cousseau Antoun Yaacoub Lionel Prevost MQ 23 0 0 12 May 2025
GuidedQuant: Large Language Model Quantization via Exploiting End Loss Guidance Jinuk Kim Marwa El Halabi W. Park Clemens JS Schaefer Deokjae Lee Yeonhong Park Jae W. Lee Hyun Oh Song MQ 34 0 0 11 May 2025
Quantization Error Propagation: Revisiting Layer-Wise Post-Training Quantization Yamato Arai Yuma Ichikawa MQ 31 0 0 13 Apr 2025
Benchmarking Post-Training Quantization in LLMs: Comprehensive Taxonomy, Unified Evaluation, and Comparative Analysis J. Zhao Hao Wu Miao Zhang Yuzhang Shang Xuebo Liu Yaowei Wang Min Zhang Liqiang Nie MQ 60 1 0 18 Feb 2025
Scaling Laws for Floating Point Quantization Training Xingchen Sun Shuaipeng Li Ruobing Xie Weidong Han Kan Wu ... Yangyu Tao Zhanhui Kang C. Xu Di Wang Jie Jiang MQ AIFin 60 0 0 05 Jan 2025
Multilingual Brain Surgeon: Large Language Models Can be Compressed Leaving No Language Behind Hongchuan Zeng Hongshen Xu Lu Chen Kai Yu 51 5 0 06 Apr 2024
A Simple and Effective Pruning Approach for Large Language Models Mingjie Sun Zhuang Liu Anna Bair J. Zico Kolter 62 355 0 20 Jun 2023
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
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 141 684 0 31 Jan 2021
Scaling Laws for Neural Language Models Jared Kaplan Sam McCandlish T. Henighan Tom B. Brown B. Chess R. Child Scott Gray Alec Radford Jeff Wu Dario Amodei 246 4,489 0 23 Jan 2020