A Non-Vector Retrieval-Augmented Generation Model for External Time-Relevant Corpus Extraction

Large language models (LLMs) have emerged as a powerful tool in the natural language process, allowing information extraction and answer generation from pre-trained databases. Regarding untrained external corpus, the retrieval-augmented generation (RAG) techniques enable quick establishing of databa

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Published
2025-01-01
DOI
https://doi.org/10.4108/eai.21-11-2024.2354622
Primary Topic
Topic Modeling
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article
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article

A Non-Vector Retrieval-Augmented Generation Model for External Time-Relevant Corpus Extraction

Jiaojing You
Topic Modeling
article

A Non-Vector Retrieval-Augmented Generation Model for External Time-Relevant Corpus Extraction

Jiaojing You
article en

Abstract

Large language models (LLMs) have emerged as a powerful tool in the natural language process, allowing information extraction and answer generation from pre-trained databases. Regarding untrained external corpus, the retrieval-augmented generation (RAG) techniques enable quick establishing of databa

South China University of Technology (CN)
Openalex Percentile: Top 98%
Topic Modeling
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A Non-Vector Retrieval-Augmented Generation Model for External Time-Relevant Corpus Extraction — Jiaojing You · (2025) | TGRS Research Map | TGRS