Transformers for Tabular Data Representation: A Tutorial on Models and Applications
Summary: Tutorial surveying transformer-based representations for tabular data, detailing how LMs adapt to relational tables and modeling limits. Outlines data-management applications and a call for DB researchers to engage with tabular transformers. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Gilbert Badaro (EURECOM)
- 2. Paolo Papotti (EURECOM)
BibTeX Citation
@article{badaro_vldb22,
title = {{Transformers for Tabular Data Representation: A Tutorial on Models and Applications}},
author = {Badaro, Gilbert and Papotti, Paolo},
journal = {PVLDB},
series = {{VLDB} '22},
volume = {15},
number = {12},
pages = {3746--3749},
doi = {10.14778/3554821.3554890},
url = {https://doi.org/10.14778/3554821.3554890},
year = {2022}
}
Incoming Citations (Sorted by Pagerank)
Showing 13 of 13 citing papers.
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Outgoing Citations (Sorted by Pagerank)
Showing 7 of 7 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 134 | Deep Entity Matching with Pre-Trained Language Models | 2021 | VLDB | 0.00030043481 |
| 377 | TURL: Table Understanding through Representation Learning | 2021 | VLDB | 0.00019570264 |
| 1,391 | Creating Embeddings of Heterogeneous Relational Datasets for Data Integration Tasks | 2020 | SIGMOD | 0.00010816237 |
| 1,780 | Annotating Columns with Pre-trained Language Models | 2022 | SIGMOD | 9.6560923e-05 |
| 1,991 | RPT: Relational Pre-trained Transformer Is Almost All You Need towards Democratizing Data Preparation | 2021 | VLDB | 9.2383849e-05 |
| 3,282 | A Deep Dive into Deep Learning Approaches for Text-to-SQL Systems | 2021 | SIGMOD | 7.4563046e-05 |
| 11,855 | Pythia: Unsupervised Generation of Ambiguous Textual Claims from Relational Data | 2022 | SIGMOD | 4.9793485e-05 |
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