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Experimental Analysis of Large-scale Learnable Vector Storage
  Compression

Experimental Analysis of Large-scale Learnable Vector Storage Compression

27 November 2023
Hailin Zhang
Penghao Zhao
Xupeng Miao
Yingxia Shao
Zirui Liu
Tong Yang
Bin Cui
ArXivPDFHTML

Papers citing "Experimental Analysis of Large-scale Learnable Vector Storage Compression"

10 / 10 papers shown
Title
Zero-Indexing Internet Search Augmented Generation for Large Language Models
Zero-Indexing Internet Search Augmented Generation for Large Language Models
Guangxin He
Zonghong Dai
Jiangcheng Zhu
Binqiang Zhao
Qicheng Hu
Chenyue Li
You Peng
Chen Wang
Binhang Yuan
67
0
0
31 Dec 2024
A Thorough Performance Benchmarking on Lightweight Embedding-based Recommender Systems
A Thorough Performance Benchmarking on Lightweight Embedding-based Recommender Systems
Hung Vinh Tran
Tong Chen
Quoc Viet Hung Nguyen
Zi-Rui Huang
Lizhen Cui
Hongzhi Yin
41
1
0
25 Jun 2024
Surge Phenomenon in Optimal Learning Rate and Batch Size Scaling
Surge Phenomenon in Optimal Learning Rate and Batch Size Scaling
Shuaipeng Li
Penghao Zhao
Hailin Zhang
Xingwu Sun
Hao Wu
...
Zheng Fang
Jinbao Xue
Yangyu Tao
Bin Cui
Di Wang
22
6
0
23 May 2024
Retrieval-Augmented Generation for AI-Generated Content: A Survey
Retrieval-Augmented Generation for AI-Generated Content: A Survey
Penghao Zhao
Hailin Zhang
Qinhan Yu
Zhengren Wang
Yunteng Geng
Fangcheng Fu
Ling Yang
Wentao Zhang
Jie Jiang
Bin Cui
3DV
115
224
0
29 Feb 2024
CAFE: Towards Compact, Adaptive, and Fast Embedding for Large-scale
  Recommendation Models
CAFE: Towards Compact, Adaptive, and Fast Embedding for Large-scale Recommendation Models
Hailin Zhang
Zirui Liu
Boxuan Chen
Yikai Zhao
Tong Zhao
Tong Yang
Bin Cui
21
10
0
06 Dec 2023
RecShard: Statistical Feature-Based Memory Optimization for
  Industry-Scale Neural Recommendation
RecShard: Statistical Feature-Based Memory Optimization for Industry-Scale Neural Recommendation
Geet Sethi
Bilge Acun
Niket Agarwal
Christos Kozyrakis
Caroline Trippel
Carole-Jean Wu
47
66
0
25 Jan 2022
Learnable Embedding Sizes for Recommender Systems
Learnable Embedding Sizes for Recommender Systems
Siyi Liu
Chen Gao
Yihong Chen
Depeng Jin
Yong Li
59
82
0
19 Jan 2021
Learning to Embed Categorical Features without Embedding Tables for
  Recommendation
Learning to Embed Categorical Features without Embedding Tables for Recommendation
Wang-Cheng Kang
D. Cheng
Tiansheng Yao
Xinyang Yi
Ting-Li Chen
Lichan Hong
Ed H. Chi
LMTD
CML
DML
45
68
0
21 Oct 2020
RocketQA: An Optimized Training Approach to Dense Passage Retrieval for
  Open-Domain Question Answering
RocketQA: An Optimized Training Approach to Dense Passage Retrieval for Open-Domain Question Answering
Yingqi Qu
Yuchen Ding
Jing Liu
Kai Liu
Ruiyang Ren
Xin Zhao
Daxiang Dong
Hua-Hong Wu
Haifeng Wang
RALM
OffRL
214
593
0
16 Oct 2020
Distributed Hierarchical GPU Parameter Server for Massive Scale Deep
  Learning Ads Systems
Distributed Hierarchical GPU Parameter Server for Massive Scale Deep Learning Ads Systems
Weijie Zhao
Deping Xie
Ronglai Jia
Yulei Qian
Rui Ding
Mingming Sun
P. Li
MoE
57
150
0
12 Mar 2020
1