ExplAIner is a layered first-order logic that expresses major XAI explanation queries over Boolean models with evaluation in the Boolean hierarchy and computation in FP^NP.
1995.Foundations of Databases
4 Pith papers cite this work. Polarity classification is still indexing.
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Pith papers citing it
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2026 4representative citing papers
Gradient-guided rewiring of foreign-key edges in relational databases degrades GNN predictions on regression tasks while preserving schema integrity constraints.
SPARQL, multiset Datalog, and multiset relational algebra are expressively equivalent for AND, UNION, FILTER, EXCEPT, and SELECT.
The paper introduces GO-FDs and graph-native normal forms that push redundancy out of labeled property graphs, covering not just node properties but also edge properties.
citing papers explorer
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ExplAIner: A Declarative Query Language for Explaining Classification Models
ExplAIner is a layered first-order logic that expresses major XAI explanation queries over Boolean models with evaluation in the Boolean hierarchy and computation in FP^NP.
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Structural Adversarial Attacks on Relational Deep Learning under Integrity Constraints
Gradient-guided rewiring of foreign-key edges in relational databases degrades GNN predictions on regression tasks while preserving schema integrity constraints.
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Multiset semantics in SPARQL, Relational Algebra and Datalog
SPARQL, multiset Datalog, and multiset relational algebra are expressively equivalent for AND, UNION, FILTER, EXCEPT, and SELECT.
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Graph-Native Normalization
The paper introduces GO-FDs and graph-native normal forms that push redundancy out of labeled property graphs, covering not just node properties but also edge properties.