OREO: Detection of Cherry-picked Generalizations
Summary: OREO detects cherry-picked generalizations by refining aggregate queries to assess their validity. It provides a support score and surfaces counterexamples and alternative statements, enabling interactive validation and explanation of data generalizations. (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. Yin Lin
- 2. Brit Youngmann
- 3. Yuval Moskovitch
- 4. H. V. Jagadish
- 5. Tova Milo
Incoming Citations (Sorted by Pagerank)
Showing 1 of 1 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 10,747 | Finding Convincing Views to Endorse a Claim | 2025 | VLDB | 4.1905499e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 5 of 5 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 3,343 | Toward Computational Fact-Checking | 2014 | VLDB | 7.196079e-05 |
| 3,687 | On Detecting Cherry-picked Trendlines | 2020 | VLDB | 6.8376481e-05 |
| 4,819 | Scrutinizer: Fact Checking Statistical Claims | 2020 | VLDB | 5.8951e-05 |
| 4,974 | Verifying Text Summaries of Relational Data Sets | 2019 | SIGMOD | 5.7877104e-05 |
| 11,422 | On Detecting Cherry-picked Generalizations | 2022 | VLDB | 4.1905499e-05 |
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