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TabulaX: Leveraging Large Language Models for Multi-Class Table Transformations
Summary: TabulaX classifies columns into string, numerical, algorithmic, or general transformations, then uses LLMs to synthesize tailored, human-interpretable formulas/code. It broadens transformation coverage and improves accuracy over prior automation methods on real-world data.
(summarized by gpt-5.6-luna on Jul 24 2026)
Paper ID
h6c344460b4e7be01
Venue
VLDB
Year
2025
Pagerank
5.4228804e-05
Overall Rank
7,933 | 46.69%
DOI
10.14778/3749646.3749657
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(CC BY-NC-ND 4.0)
Incoming Non-self Citations Over Time
BibTeX Citation
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@article{nobari_vldb25,
title = {{TabulaX: Leveraging Large Language Models for Multi-Class Table Transformations}},
author = {Nobari, Arash Dargahi and Rafiei, Davood},
journal = {PVLDB},
series = {{VLDB} '25},
volume = {18},
number = {11},
pages = {3826--3839},
doi = {10.14778/3749646.3749657},
url = {https://doi.org/10.14778/3749646.3749657},
year = {2025}
}
Incoming Citations (Sorted by Pagerank)
Showing 4 of 4 citing papers.
Outgoing Citations (Sorted by Pagerank)
Showing 18 of 18 cited papers.
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RPT: Relational Pre-trained Transformer Is Almost All You Need towards Democratizing Data Preparation
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Open Data Integration
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2017
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2,744
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4,159
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4,204
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2015
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4,972
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5,100
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5,686
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