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Counterfactual Explanation Analytics: Empowering Lay Users to Take Action Against Consequential Automated Decisions

Summary: FACET introduces interactive, robust counterfactual region explanations (vs static point counterfactuals) that surface multiple personalized, actionable modification options a lay user can realistically enact. Web dashboard demonstrates exploration, comparison and plan-building for loan decisions. (summarized by gpt-5-mini on Feb 09 2026)

Paper ID
13654
Venue
VLDB
Year
2024
Pagerank
4.1945683e-05
Overall Rank
11,107 | 22.74%
DOI
10.14778/3685800.3685872

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Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.

Rank Cited Paper Year Venue Pagerank
129 The X-tree: An Index Structure for High-Dimensional Data 1996 VLDB 0.0004429571
5,997 FACET: Robust Counterfactual Explanation Analytics 2023 SIGMOD 5.2415551e-05
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