TabEE: Tabular Embeddings Explanations

Summary: TabEE offers model-agnostic explanations for tabular embeddings, enabling local/global interpretation and flaw detection. It enables cross-model comparison to uncover data biases, aiding credible embedding design across databases. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID: 6943
Venue: SIGMOD
Year: 2024
Pagerank: 5.3512451e-05
Overall Rank: 8,888 | 39.03%
DOI: 10.1145/3639329

Incoming Non-self Citations Over Time

Authors

1. Roni Copul (Tel Aviv University)
2. Nave Frost (eBay)
3. Tova Milo (Tel Aviv University)
4. Kathy Razmadze (Tel Aviv University)

BibTeX Citation

@inproceedings{copul_sigmod24,
        title = {{TabEE: Tabular Embeddings Explanations}},
        author = {Copul, Roni and Frost, Nave and Milo, Tova and Razmadze, Kathy},
        series = {{SIGMOD} '24},
        booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
        publisher = {Association for Computing Machinery},
        doi = {10.1145/3639329},
        url = {https://dl.acm.org/doi/10.1145/3639329},
        year = {2024}
}

Incoming Citations (Sorted by Pagerank)

Showing 5 of 5 citing papers.

Rank	Citing Paper	Year	Venue	Pagerank
10,313	Differentially Private Explanations for Clusters	2026	SIGMOD	5.093636e-05
10,390	AixelNet: A Pre-trained Model with Table-aware Adaptation for Structured Data Prediction	2026	SIGMOD	5.093636e-05
11,098	SDEcho: Efficient Explanation of Aggregated Sequence Difference	2025	VLDB	5.093636e-05
13,304	Demonstration of DPClustX: Differentially Private Explanations for Clusters	2025	SIGMOD	-
13,367	Demonstrating TabEE: Tabular Embedding Explanations	2024	VLDB	-

Outgoing Citations (Sorted by Pagerank)

Showing 11 of 11 cited papers.

Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.

Rank	Cited Paper	Year	Venue	Pagerank
1,827	G-OLA: Generalized On-Line Aggregation for Interactive Analysis on Big Data	2015	SIGMOD	9.6690206e-05
2,161	DIFF: A Relational Interface for Large-Scale Data Explanation	2019	VLDB	9.0606664e-05
2,264	Exploiting Latent Information in Relational Databases via Word Embedding and Application to Degrees of Disclosure	2019	CIDR	8.8419988e-05
3,072	Lux: Always-on Visualization Recommendations for Exploratory Dataframe Workflows	2022	VLDB	7.7873864e-05
3,132	Extracting Top-K Insights from Multi-dimensional Data	2017	SIGMOD	7.7246394e-05
4,249	Exploratory Keyword Search with Interactive Input	2015	SIGMOD	6.8042877e-05
4,628	QuickInsights: Quick and Automatic Discovery of Insights from Multi-Dimensional Data	2019	SIGMOD	6.5962102e-05
7,003	Guided Exploration of Data Summaries	2022	VLDB	5.7278883e-05
7,399	ExRank: An Exploratory Ranking Interface	2016	VLDB	5.6255964e-05
8,184	FEDEX: An Explainability Framework for Data Exploration Steps	2022	VLDB	5.4709725e-05
9,438	SubTab: Data Exploration with Informative Sub-Tables	2022	SIGMOD	5.2687297e-05

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10	13,367	Demonstrating TabEE: Tabular Embedding Explanations	2024	VLDB