Back to papers
Summarized Causal Explanations For Aggregate Views
Summary: CauSumX generates summarized causal explanations for entire aggregate views (group-by averages) via a causal DAG. It uses an optimization with Apriori+LP rounding to select group-specific causal treatments; scalable to high-dimensional data and outperforms prior work in usefulness and realism.
(summarized by gpt-5-nano on Feb 09 2026)
Paper ID
h829d8e94eb69e145
Venue
SIGMOD
Year
2024
Pagerank
5.7635046e-05
Overall Rank
6,450 | 56.77%
DOI
10.1145/3639328
Incoming Non-self Citations Over Time
BibTeX Citation
@inproceedings{youngmann_sigmod24,
title = {{Summarized Causal Explanations For Aggregate Views}},
author = {Youngmann, Brit and Cafarella, Michael and Gilad, Amir and Roy, Sudeepa},
series = {{SIGMOD} '24},
booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
publisher = {Association for Computing Machinery},
doi = {10.1145/3639328},
url = {https://dl.acm.org/doi/10.1145/3639328},
year = {2024}
}
Incoming Citations (Sorted by Pagerank)
Showing 12 of 12 citing papers.
Rank
Citing Paper
Year
Venue
Pagerank
9,265
Causal DAG Summarization 2025
VLDB
5.1860131e-05
9,990
Fair and Actionable Causal Prescription Ruleset 2025
SIGMOD
5.0845476e-05
10,660
Privacy-preserving and Verifiable Causal Prescriptive Analytics 2026
SIGMOD
4.9605343e-05
10,697
Causal Explanations for Disparate Trends: Where and Why? 2026
SIGMOD
4.9605343e-05
10,760
Stress-Testing Causal Claims via Cardinality Repairs 2026
SIGMOD
4.9605343e-05
10,870
Finding Non-Redundant Simpson's Paradox in Multidimensional Data 2026
VLDB
4.9605343e-05
11,061
SubCure: A System for Stress-Testing Causal Conclusions Using Cardinality Repairs 2026
VLDB
4.9605343e-05
11,209
CausaLens: A System for Summarizing Causal DAGs 2025
SIGMOD
4.9605343e-05
11,211
CauSumX: Summarized Causal Explanations For Group-By-Average Queries 2025
SIGMOD
4.9605343e-05
11,405
What If: Causal Analysis with Graph Databases 2025
VLDB
4.9605343e-05
11,415
Suna: Scalable Causal Confounder Discovery over Relational Data 2025
VLDB
4.9605343e-05
11,508
SDEcho: Efficient Explanation of Aggregated Sequence Difference 2025
VLDB
4.9605343e-05
Outgoing Citations (Sorted by Pagerank)
Showing 27 of 27 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
Rank
Cited Paper
Year
Venue
Pagerank
29
Fast Algorithms for Mining Association Rules 1994
VLDB
0.00051028332
191
Scorpion: Explaining Away Outliers in Aggregate Queries 2013
VLDB
0.0002578784
389
Why Not? 2009
SIGMOD
0.00019254758
581
The Complexity of Causality and Responsibility for Query Answers and non-Answers 2011
VLDB
0.00016042765
672
A Formal Approach to Finding Explanations for Database Queries 2014
SIGMOD
0.00014903109
811
Provenance for Aggregate Queries 2011
PODS
0.00013713646
879
Interpretable and Informative Explanations of Outcomes 2015
VLDB
0.00013255435
929
Intelligent Rollups in Multidimensional OLAP Data 2001
VLDB
0.000130092
2,233
Explaining Query Answers with Explanation-Ready Databases 2016
VLDB
8.7844607e-05
2,328
Causal Relational Learning 2020
SIGMOD
8.6206869e-05
2,361
Bias in OLAP Queries: Detection, Explanation, and Removal (Or Think Twice About Your AVG-Query) 2018
SIGMOD
8.5605216e-05
2,444
The Generalized MDL Approach for Summarization 2002
VLDB
8.4450845e-05
2,734
The Impact of Negation on the Complexity of the Shapley Value in Conjunctive Queries 2020
PODS
8.0650095e-05
3,472
Quotient Cube: How to Summarize the Semantics of a Data Cube 2002
VLDB
7.2574793e-05
4,298
MDL Summarization with Holes 2005
VLDB
6.6640493e-05
4,577
HYPER: Hypothetical Reasoning With What-If and How-To Queries Using a Probabilistic Causal Approach 2022
SIGMOD
6.5111757e-05
4,742
Going Beyond Provenance: Explaining Query Answers with Pattern-based Counterbalances 2019
SIGMOD
6.4285195e-05
4,752
Interactive Summarization and Exploration of Top Aggregate Query Answers 2018
VLDB
6.4226993e-05
4,865
High-Level Why-Not Explanations using Ontologies 2015
PODS
6.3619008e-05
4,881
Constructing and Exploring Composite Items 2010
SIGMOD
6.3565335e-05
5,008
XInsight: eXplainable Data Analysis Through The Lens of Causality 2023
SIGMOD
6.3049458e-05
5,556
Putting Things into Context: Rich Explanations for Query Answers using Join Graphs 2021
SIGMOD
6.0705311e-05
6,196
Causal Data Integration 2023
VLDB
5.8366172e-05
7,173
Guided Exploration of Data Summaries 2022
VLDB
5.578213e-05
8,375
FEDEX: An Explainability Framework for Data Exploration Steps 2022
VLDB
5.3280107e-05
8,910
DPXPlain: Privately Explaining Aggregate Query Answers 2023
VLDB
5.2369069e-05
9,612
On Detecting Cherry-picked Generalizations 2022
VLDB
5.1376962e-05
Semantically Similar Papers