Demonstrating TabEE: Tabular Embedding Explanations
Summary: TabEE: framework that explains tabular embedding models by identifying cohorts in embedding space and mapping them to key original-attribute distribution shifts that characterize embedding geometry. Black-box compatible with any tabular embedding, enables local/global explanations, model comparison, debugging and bias detection. (summarized by gpt-5-mini on Feb 09 2026)
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Authors
- 1. Roni Copul
- 2. Nave Frost
- 3. Tova Milo
- 4. Kathy Razmadze
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Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 8,388 | FEDEX: An Explainability Framework for Data Exploration Steps | 2022 | VLDB | 4.5297787e-05 |
| 8,862 | TabEE: Tabular Embeddings Explanations | 2024 | SIGMOD | 4.4331977e-05 |
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