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LLM for Data Management

Summary: Tutorial surveying use of LLMs to optimize data management, advocating retrieval-augmented generation (RAG) to curb hallucination, vector databases to cut latency, and LLM-agent multi-round pipelines for complex workflows. Focuses on applications (query rewrite, DB diagnosis, NL analytics), implementation trade-offs (cost, accuracy, latency), and open research challenges. (summarized by gpt-5-mini on Feb 09 2026)

Paper ID
13807
Venue
VLDB
Year
2024
Pagerank
5.9774273e-05
Overall Rank
6,101 | 58.15%
DOI
10.14778/3685800.3685838

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@article{li_vldb24,
        title = {{LLM for Data Management}},
        author = {Li, Guoliang and Zhou, Xuanhe and Zhao, Xinyang},
        journal = {PVLDB},
        series = {{VLDB} '24},
        volume = {17},
        number = {12},
        pages = {4213--4216},
        doi = {10.14778/3685800.3685838},
        url = {https://doi.org/10.14778/3685800.3685838},
        year = {2024}
}

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