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CauSumX: Summarized Causal Explanations For Group-By-Average Queries

Summary: CauSumX yields concise, causal explanations for group-by-average queries, aiding interpretation of high-dimensional results. It uses background causal knowledge and an efficient algorithm to reveal key cause-effect drivers of cross-group variation. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
7199
Venue
SIGMOD
Year
2025
Pagerank
5.093636e-05
Overall Rank
10,710 | 26.52%
DOI
10.1145/3722212.3725088

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Authors

BibTeX Citation

@inproceedings{levy_sigmod25,
        title = {{CauSumX: Summarized Causal Explanations For Group-By-Average Queries}},
        author = {Levy, Nativ and Cafarella, Michael John and Gilad, Amir and Roy, Sudeepa and Youngmann, Brit},
        series = {{SIGMOD} '25},
        booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
        publisher = {Association for Computing Machinery},
        doi = {10.1145/3722212.3725088},
        url = {https://dl.acm.org/doi/10.1145/3722212.3725088},
        year = {2025}
}

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