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From BERT to GPT-3 Codex: Harnessing the Potential of Very Large Language Models for Data Management
Summary: Survey of very large language models (VLLMs) for data management, detailing usage in DB tasks with minimal fine-tuning. Explores Codex-style code generation, libraries/APIs, and LM-based architectures and integration with traditional systems.
(summarized by gpt-5-nano on Feb 09 2026)
Paper ID
hf3dbc53009b80884
Venue
VLDB
Year
2022
Pagerank
6.5957098e-05
Overall Rank
4,444 | 70.14%
DOI
10.14778/3554821.3554896
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(CC BY-NC-ND 4.0)
Incoming Non-self Citations Over Time
BibTeX Citation
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@article{trummer_vldb22,
title = {{From BERT to GPT-3 Codex: Harnessing the Potential of Very Large Language Models for Data Management}},
author = {Trummer, Immanuel},
journal = {PVLDB},
series = {{VLDB} '22},
volume = {15},
number = {12},
pages = {3770--3773},
doi = {10.14778/3554821.3554896},
url = {https://doi.org/10.14778/3554821.3554896},
year = {2022}
}
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