Schuyler: Self-Supervised Clustering of Tables in Relational Databases
Summary: Schuyler clusters relational tables using structural features and self-supervised LLM embeddings trained with triplet loss. Requiring no labels, it generalizes across databases and outperforms prior methods by 0.13 ARI and 0.10 AMI on a five-database benchmark. (summarized by gpt-5.6-luna on Jul 24 2026)
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Authors
- 1. Lukas Laskowski (Hasso Plattner Institute; University of Potsdam)
- 2. Fabian Panse (University of Augsburg)
- 3. Michael Hladik (SAP)
- 4. Jan Portisch (SAP)
- 5. Felix Naumann (Hasso Plattner Institute; University of Potsdam)
BibTeX Citation
@article{laskowski_vldb26,
title = {{Schuyler: Self-Supervised Clustering of Tables in Relational Databases}},
author = {Laskowski, Lukas and Panse, Fabian and Hladik, Michael and Portisch, Jan and Naumann, Felix},
journal = {PVLDB},
series = {{VLDB} '26},
volume = {19},
number = {4},
pages = {657--669},
doi = {10.14778/3785297.3785307},
url = {https://doi.org/10.14778/3785297.3785307},
year = {2026}
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Outgoing Citations (Sorted by Pagerank)
Showing 4 of 4 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 291 | OPTICS: Ordering Points To Identify the Clustering Structure | 1999 | SIGMOD | 0.00022264197 |
| 1,532 | Summarizing Relational Databases | 2009 | VLDB | 0.00010472227 |
| 4,228 | Discovering Topical Structures of Databases | 2008 | SIGMOD | 6.819835e-05 |
| 4,957 | General purpose database summarization | 2005 | VLDB | 6.4288409e-05 |
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