LPLM: A Neural Language Model for Cardinality Estimation of LIKE-Queries
Summary: LPLM is a neural language model for LIKE-pattern cardinality estimation, with a novel pattern language and distribution for in-between wildcards. A data-generation method trains it; it outperforms prior work on Q-error with similar runtime/memory. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
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Incoming Citations (Sorted by Pagerank)
Showing 9 of 9 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 9,726 | Cardinality Estimation of LIKE Predicate Queries using Deep Learning | 2025 | SIGMOD | 4.2943379e-05 |
| 9,728 | SPACE: Cardinality Estimation for Path Queries Using Cardinality-Aware Sequence-based Learning | 2025 | SIGMOD | 4.2942813e-05 |
| 9,825 | Athena: An Effective Learning-based Framework for Query Optimizer Performance Improvement | 2025 | SIGMOD | 4.2751057e-05 |
| 9,945 | SSCard: Substring Cardinality Estimation using Suffix Tree-Guided Learned FM-Index | 2026 | SIGMOD | 4.2432653e-05 |
| 10,216 | The Case For Language Model Approximated LIKE Predicate | 2026 | SIGMOD | 4.1945683e-05 |
| 10,219 | Practical Parameterized Query Optimization via Efficient Plan Reuse and List-wise Ranking | 2026 | SIGMOD | 4.1945683e-05 |
| 10,590 | ACE: A Cardinality Estimator for Set-Valued Queries | 2025 | VLDB | 4.1945683e-05 |
| 10,751 | PAR2QO: Parametric Penalty-Aware Robust Query Optimization | 2025 | VLDB | 4.1945683e-05 |
| 10,880 | RankPQO: Learning-to-Rank for Parametric Query Optimization | 2025 | VLDB | 4.1945683e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 21 of 21 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
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