MithraCoverage: A System for Investigating Population Bias for Intersectional Fairness
Summary: MithraCoverage identifies intersectional subgroups with inadequate representation by coverage over attributes. A web-based visualization lets data scientists explore datasets and diagnose population bias via underrepresented intersectional groups. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Zhongjun Jin
- 2. Mengjing Xu
- 3. Chenkai Sun
- 4. Abolfazl Asudeh
- 5. H. V. Jagadish
Incoming Citations (Sorted by Pagerank)
Showing 9 of 9 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 1,940 | SliceLine: Fast, Linear-Algebra-based Slice Finding for ML Model Debugging | 2021 | SIGMOD | 0.00010020173 |
| 3,162 | Looking for Trouble: Analyzing Classifier Behavior via Pattern Divergence | 2021 | SIGMOD | 7.4589576e-05 |
| 5,976 | Responsible Data Integration: Next-generation Challenges | 2022 | SIGMOD | 5.245976e-05 |
| 6,467 | Tailoring Data Source Distributions for Fairness-aware Data Integration | 2021 | VLDB | 5.0528156e-05 |
| 6,892 | Identifying Insufficient Data Coverage for Ordinal Continuous-Valued Attributes | 2021 | SIGMOD | 4.8925683e-05 |
| 7,685 | Fairly Evaluating and Scoring Items in a Data Set | 2020 | VLDB | 4.6788921e-05 |
| 7,851 | Consistent Range Approximation for Fair Predictive Modeling | 2023 | VLDB | 4.6353072e-05 |
| 11,218 | Equitable Top-k Results for Long Tail Data | 2023 | SIGMOD | 4.1945683e-05 |
| 11,523 | How Divergent Is Your Data? | 2021 | VLDB | 4.1945683e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 0 of 0 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|
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