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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
- 6881
- Venue
- SIGMOD
- Year
- 2024
- Pagerank
- 4.4331977e-05
- Overall Rank
- 8,862 | 38.35%
- DOI
-
10.1145/3639329
Incoming Non-self Citations Over Time
Incoming Citations (Sorted by Pagerank)
Showing 5 of 5 citing papers.
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 |
| 1,251 |
Exploiting Latent Information in Relational Databases via Word Embedding and Application to Degrees of Disclosure |
2019 |
CIDR |
0.00013035649 |
| 2,154 |
DIFF: A Relational Interface for Large-Scale Data Explanation |
2019 |
VLDB |
9.4208667e-05 |
| 2,355 |
G-OLA: Generalized On-Line Aggregation for Interactive Analysis on Big Data |
2015 |
SIGMOD |
8.9677847e-05 |
| 3,393 |
Lux: Always-on Visualization Recommendations for Exploratory Dataframe Workflows |
2022 |
VLDB |
7.1483239e-05 |
| 3,546 |
Extracting Top-K Insights from Multi-dimensional Data |
2017 |
SIGMOD |
6.9870745e-05 |
| 4,331 |
Exploratory Keyword Search with Interactive Input |
2015 |
SIGMOD |
6.2836568e-05 |
| 5,217 |
QuickInsights: Quick and Automatic Discovery of Insights from Multi-Dimensional Data |
2019 |
SIGMOD |
5.6227959e-05 |
| 7,222 |
Guided Exploration of Data Summaries |
2022 |
VLDB |
4.797186e-05 |
| 7,565 |
ExRank: An Exploratory Ranking Interface |
2016 |
VLDB |
4.7091711e-05 |
| 8,388 |
FEDEX: An Explainability Framework for Data Exploration Steps |
2022 |
VLDB |
4.5297787e-05 |
| 9,262 |
SubTab: Data Exploration with Informative Sub-Tables |
2022 |
SIGMOD |
4.368964e-05 |
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- |
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4.427232e-05 |
| 10,090 |
Integrating Vector Databases across Embedding Models |
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| 1,914 |
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| 9,399 |
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| 6,800 |
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| 6,092 |
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VLDB |
5.2138566e-05 |
| 6,894 |
TableDC: Deep Clustering for Tabular Data |
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SIGMOD |
4.8925595e-05 |
| 10,524 |
Understanding the Black Box: A Deep Empirical Dive into Shapley Value Approximations for Tabular Data |
2025 |
SIGMOD |
4.1945683e-05 |
| 13,163 |
Demonstrating TabEE: Tabular Embedding Explanations |
2024 |
VLDB |
- |