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Demonstration of DB-GPT: Next Generation Data Interaction System Empowered by Large Language Models

Summary: DB-GPT: a product-ready Python library embedding LLMs into data interaction, from Text-to-SQL to generative analytics via a Multi-Agent framework and Agentic Workflow Expression Language (AWEL). SMMF enables private-LLM support and secure local/distributed/cloud deployment; code on GitHub. (summarized by gpt-5-mini on Feb 09 2026)

Paper ID
13846
Venue
VLDB
Year
2024
Pagerank
5.2755515e-05
Overall Rank
9,391 | 35.57%
DOI
10.14778/3685800.3685876

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@article{xue_vldb24,
        title = {{Demonstration of DB-GPT: Next Generation Data Interaction System Empowered by Large Language Models}},
        author = {Xue, Siqiao and Qi, Danrui and Jiang, Caigao and Cheng, Fangyin and Chen, Keting and Zhang, Zhiping and Zhang, Hongyang and Wei, Ganglin and Zhao, Wang and Zhou, Fan and Yi, Hong and Liu, Shaodong and Yang, Hongjun and Chen, Faqiang},
        journal = {PVLDB},
        series = {{VLDB} '24},
        volume = {17},
        number = {12},
        pages = {4365--4368},
        doi = {10.14778/3685800.3685876},
        url = {https://doi.org/10.14778/3685800.3685876},
        year = {2024}
}

Incoming Citations (Sorted by Pagerank)

Showing 1 of 1 citing papers.

Rank Citing Paper Year Venue Pagerank
10,510 NL2SQLBench: A Modular Benchmarking Framework for LLM-Enabled NL2SQL Solutions 2026 VLDB 5.093636e-05
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Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.

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