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Summary: Per-table transformers learn the joint attribute distribution to yield a multidimensional sketch for selections. This enables join cardinality with arbitrary filters, scales linearly with table count, and matches exact-sketch accuracy with lower overhead. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
6875
Venue
SIGMOD
Year
2024
Pagerank
4.3143499e-05
Overall Rank
9,628 | 33.02%
DOI
10.1145/3639321

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