EnumGRPO is a self-improving optimizer for agentic query execution that reduces LLM-operator costs by ~317x while improving accuracy by 18% over a hybrid baseline across four databases.
VLDB Endow.14, 1 (2020), 50–60
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EcoTable is the first NL-based data integration framework that builds a join-likelihood graph, uses two-stage schema linking and Steiner tree search to find paths, then generates transformations with LLMs, reporting >30% accuracy gain and 5x lower cost on four real-world datasets.
MoRER builds an ER model repository via feature distribution clustering of tasks, achieving competitive results with limited labels versus active learning, transfer learning, and self-supervised methods on three multi-source datasets.
citing papers explorer
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Cost-Aware Optimization for Agentic Query Execution
EnumGRPO is a self-improving optimizer for agentic query execution that reduces LLM-operator costs by ~317x while improving accuracy by 18% over a hybrid baseline across four databases.
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EcoTable: Cost-effective Table Integration in Data Lakes for Natural Language Queries
EcoTable is the first NL-based data integration framework that builds a join-likelihood graph, uses two-stage schema linking and Steiner tree search to find paths, then generates transformations with LLMs, reporting >30% accuracy gain and 5x lower cost on four real-world datasets.
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Efficient Model Repository for Entity Resolution: Construction, Search, and Integration
MoRER builds an ER model repository via feature distribution clustering of tasks, achieving competitive results with limited labels versus active learning, transfer learning, and self-supervised methods on three multi-source datasets.