Advancing Fact Attribution for Query Answering: Aggregate Queries and Novel Algorithms
Summary: First practical method to compute Banzhaf and Shapley contributions for aggregate queries (beyond SPJUU). Two optimizations—grouping equal-contribution tuples and using lineage gradients to amortize cost—yield up to 1000× speedups and scale to million-instance tests. (summarized by gpt-5-mini on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Omer Abramovich (Tel Aviv University)
- 2. Daniel Deutch (Tel Aviv University)
- 3. Nave Frost (eBay)
- 4. Ahmet Kara (Ostbayerische Technische Hochschule Regensburg)
- 5. Dan Olteanu (University of Zurich)
BibTeX Citation
@article{abramovich_vldb25,
title = {{Advancing Fact Attribution for Query Answering: Aggregate Queries and Novel Algorithms}},
author = {Abramovich, Omer and Deutch, Daniel and Frost, Nave and Kara, Ahmet and Olteanu, Dan},
journal = {PVLDB},
series = {{VLDB} '25},
volume = {18},
number = {11},
pages = {3996--4008},
doi = {10.14778/3749646.3749670},
url = {https://doi.org/10.14778/3749646.3749670},
year = {2025}
}
Incoming Citations (Sorted by Pagerank)
Showing 2 of 2 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 10,183 | Tractability Frontiers of the Shapley Value for Aggregate Conjunctive Queries | 2026 | PODS | 5.093636e-05 |
| 10,429 | Analyzing Deviations from Monotonic Trends through Database Repair | 2026 | SIGMOD | 5.093636e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 11 of 11 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
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