ResearchTrend.AI
  • Papers
  • Communities
  • Events
  • Blog
  • Pricing
Papers
Communities
Social Events
Terms and Conditions
Pricing
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2025 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 2305.12356
  4. Cited By
Integer or Floating Point? New Outlooks for Low-Bit Quantization on
  Large Language Models

Integer or Floating Point? New Outlooks for Low-Bit Quantization on Large Language Models

21 May 2023
Yijia Zhang
Lingran Zhao
Shijie Cao
Wenqiang Wang
Ting Cao
Fan Yang
Mao Yang
Shanghang Zhang
Ningyi Xu
    MQ
ArXivPDFHTML

Papers citing "Integer or Floating Point? New Outlooks for Low-Bit Quantization on Large Language Models"

2 / 2 papers shown
Title
Learning from Students: Applying t-Distributions to Explore Accurate and
  Efficient Formats for LLMs
Learning from Students: Applying t-Distributions to Explore Accurate and Efficient Formats for LLMs
Jordan Dotzel
Yuzong Chen
Bahaa Kotb
Sushma Prasad
Gang Wu
Sheng R. Li
Mohamed S. Abdelfattah
Zhiru Zhang
24
7
0
06 May 2024
FP8 Formats for Deep Learning
FP8 Formats for Deep Learning
Paulius Micikevicius
Dusan Stosic
N. Burgess
Marius Cornea
Pradeep Dubey
...
Naveen Mellempudi
S. Oberman
M. Shoeybi
Michael Siu
Hao Wu
BDL
VLM
MQ
67
121
0
12 Sep 2022
1