On Detecting Cherry-picked Generalizations
Summary: Framework for detecting and explaining cherry-picked generalizations by refining aggregate queries. Scoring metric for generalization quality, efficient score computation, and explanation tasks to reveal counterexamples and alternatives. (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 8 of 8 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 7,172 | Summarized Causal Explanations For Aggregate Views | 2024 | SIGMOD | 4.8068645e-05 |
| 9,644 | Fair and Actionable Causal Prescription Ruleset | 2025 | SIGMOD | 4.3067693e-05 |
| 10,140 | Analyzing Deviations from Monotonic Trends through Database Repair | 2026 | SIGMOD | 4.1905499e-05 |
| 10,147 | Causal Explanations for Disparate Trends: Where and Why? | 2026 | SIGMOD | 4.1905499e-05 |
| 10,213 | Stress-Testing Causal Claims via Cardinality Repairs | 2026 | SIGMOD | 4.1905499e-05 |
| 10,747 | Finding Convincing Views to Endorse a Claim | 2025 | VLDB | 4.1905499e-05 |
| 10,814 | ClaimIt: Finding Convincing Views to Endorse a Claim | 2025 | VLDB | 4.1905499e-05 |
| 11,395 | OREO: Detection of Cherry-picked Generalizations | 2022 | VLDB | 4.1905499e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 10 of 10 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 213 | Scorpion: Explaining Away Outliers in Aggregate Queries | 2013 | VLDB | 0.0003371037 |
| 247 | On the Computation of Multidimensional Aggregates | 1996 | VLDB | 0.00030923842 |
| 461 | SeeDB: Efficient Data-Driven Visualization Recommendations to Support Visual Analytics | 2015 | VLDB | 0.00022615628 |
| 1,001 | Intelligent Rollups in Multidimensional OLAP Data | 2001 | VLDB | 0.00014709145 |
| 2,816 | Bias in OLAP Queries: Detection, Explanation, and Removal (Or Think Twice About Your AVG-Query) | 2018 | SIGMOD | 8.0747683e-05 |
| 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 |
| 7,730 | AggChecker: A Fact-Checking System for Text Summaries of Relational Data Sets | 2019 | VLDB | 4.6613872e-05 |
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| Overall Rank | Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 8,663 | Advancing Fact Attribution for Query Answering: Aggregate Queries and Novel Algorithms | 2025 | VLDB | 4.4676883e-05 |
| 943 | A Formal Approach to Finding Explanations for Database Queries | 2014 | SIGMOD | 0.00015140995 |
| 9,179 | Efficient Exploration of Interesting Aggregates in RDF Graphs | 2021 | SIGMOD | 4.3793465e-05 |
| 2,544 | Aggregation and Relevance in Deductive Databases | 1991 | VLDB | 8.5646035e-05 |
| 10,747 | Finding Convincing Views to Endorse a Claim | 2025 | VLDB | 4.1905499e-05 |
| 7,730 | AggChecker: A Fact-Checking System for Text Summaries of Relational Data Sets | 2019 | VLDB | 4.6613872e-05 |
| 2,655 | Explaining Query Answers with Explanation-Ready Databases | 2016 | VLDB | 8.3638668e-05 |
| 3,343 | Toward Computational Fact-Checking | 2014 | VLDB | 7.196079e-05 |
| 3,687 | On Detecting Cherry-picked Trendlines | 2020 | VLDB | 6.8376481e-05 |
| 11,395 | OREO: Detection of Cherry-picked Generalizations | 2022 | VLDB | 4.1905499e-05 |