SemCEB is the first benchmark for cardinality estimation over semantic operators, evaluating sampling methods and Semantic Histograms on accuracy, cost, latency, and memory using 102 queries on a real-world dataset.
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cs.DB 2years
2026 2verdicts
UNVERDICTED 2representative citing papers
Semantic Histograms treat semantic image filters as implicit range queries in embedding space and use two specificity estimators whose ensemble reduces end-to-end query optimization and execution overhead by up to 86%.
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SemCEB: A Cardinality Estimation Benchmark for Semantic Operators
SemCEB is the first benchmark for cardinality estimation over semantic operators, evaluating sampling methods and Semantic Histograms on accuracy, cost, latency, and memory using 102 queries on a real-world dataset.
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Selectivity Estimation for Semantic Filters on Image Data
Semantic Histograms treat semantic image filters as implicit range queries in embedding space and use two specificity estimators whose ensemble reduces end-to-end query optimization and execution overhead by up to 86%.