CFDB: Machine Learning Model Analysis via Databases of CounterFactuals
Summary: CFDB provides a relational, queryable database of counterfactuals to unify CF generation, selection, and analysis for evolving models. With multi-level abstractions, it supports local explanations and global model insights on Lending Club loan data. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
No non-self incoming citations found for this paper in this database.
Authors
- 1. Idan Meyuhas
- 2. Aviv Ben Arie
- 3. Yair Horesh
- 4. Daniel Deutch
Incoming Citations (Sorted by Pagerank)
Showing 0 of 0 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|
Previous
Page 1 / 1
Next
Outgoing Citations (Sorted by Pagerank)
Showing 3 of 3 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 2,923 | Explaining Black-Box Algorithms Using Probabilistic Contrastive Counterfactuals | 2021 | SIGMOD | 7.8953538e-05 |
| 4,725 | GeCo: Quality Counterfactual Explanations in Real Time | 2021 | VLDB | 5.9697637e-05 |
| 11,634 | Personal Insights for Altering Decisions of Tree-based Ensembles over Time | 2020 | VLDB | 4.1945683e-05 |
Previous
Page 1 / 1
Next