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Vector Storage Based Long-term Memory Research on LLM Cover
By: Kun Li,  Xin Jing and  Chengang Jing  
Open Access
|Sep 2024

Figures & Tables

Figure 1.

VIMBank Framework

Figure 2.

Different types of memory

Figure 3.

Retrieval memory

Figure 4.

Examples from different task sets

Experimental results on various datasets

DataSetModelNoAgentReActInterActVIMBank
ALFWorldQwen2-7b48.854.760.172.3
ChatGLM346.249.255.864.9
HotpotQAQwen2-7b51.657.363.476.3
ChatGLM345.951.859.771.5
KAgentBenchQwen2-7b34.248.552.658.7
ChatGLM332.644.746.354.2

Reasoning cost of ALFWorld environment

2006001000
NoAgent63.2K164.7K334.7K
VIMBank56.8K142.6K258.3K

Experimental Environment

Experimental EnvironmentVersion
CPUIntel Core i9-10900K
GPUNVIDIA Tesla V100 PCIe
32G
LanguagePython 3.9
FrameworkLangChain
Language: English
Page range: 69 - 79
Published on: Sep 30, 2024
In partnership with: Paradigm Publishing Services
Publication frequency: 4 issues per year

© 2024 Kun Li, Xin Jing, Chengang Jing, published by Xi’an Technological University
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.