ELEET: Efficient Learned Query Execution over Text and Tables

Summary: ELEET makes text first-class via learned multi-modal operators (MMOps), enabling native joins/unions over tables and unstructured text. Replacing LLMs with a compact SLM and tailored pretraining, ELEET extracts structure with low overhead and achieves up to 575× speedups vs GPT‑4 baselines without accuracy loss. (summarized by gpt-5-mini on Feb 09 2026)

Paper ID: ha274a529b0aa2591
Venue: VLDB
Year: 2024
Pagerank: 6.1408676e-05
Overall Rank: 5,410 | 63.63%
DOI: 10.14778/3704965.3704989

Incoming Non-self Citations Over Time

Authors

1. Matthias Urban (Technical University of Darmstadt)
2. Carsten Binnig (German National Research Center for Information Technology; Technical University of Darmstadt)

BibTeX Citation

@article{urban_vldb24,
        title = {{ELEET: Efficient Learned Query Execution over Text and Tables}},
        author = {Urban, Matthias and Binnig, Carsten},
        journal = {PVLDB},
        series = {{VLDB} '24},
        volume = {17},
        number = {13},
        pages = {4867--4880},
        doi = {10.14778/3704965.3704989},
        url = {https://doi.org/10.14778/3704965.3704989},
        year = {2024}
}

Incoming Citations (Sorted by Pagerank)

Showing 7 of 7 citing papers.

Rank	Citing Paper	Year	Venue	Pagerank
8,679	Relational Deep Dive: Error-Aware Queries Over Unstructured Data	2026	VLDB	5.2905577e-05
8,997	Cut Costs, Not Accuracy: LLM-Powered Data Processing with Guarantees	2026	SIGMOD	5.2410834e-05
10,346	KathDB: Explainable Multimodal Database Management System with Human-AI Collaboration	2026	CIDR	4.9793485e-05
10,400	100x Cost & Latency Reduction: Performance Analysis of AI Query Approximation using Lightweight Proxy Models: [Experiments & Analysis]	2026	SIGMOD	4.9793485e-05
10,690	Task Cascades for Efficient Unstructured Data Processing	2026	SIGMOD	4.9793485e-05
10,800	MGRAG: Semantic Subgraph Matching and Graph-Aware Caching for Multimodal Retrieval-Augmented Generation	2026	VLDB	4.9793485e-05
10,845	Featurized-Decomposition Join: Low-Cost Semantic Joins with Guarantees	2026	VLDB	4.9793485e-05

Outgoing Citations (Sorted by Pagerank)

Showing 16 of 16 cited papers.

Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.

Rank	Cited Paper	Year	Venue	Pagerank
134	Deep Entity Matching with Pre-Trained Language Models	2021	VLDB	0.00030043481
328	Declarative Information Extraction Using Datalog with Embedded Extraction Predicates	2007	VLDB	0.00020928928
329	Can Foundation Models Wrangle Your Data?	2023	VLDB	0.00020858443
501	Language Models Enable Simple Systems for Generating Structured Views of Heterogeneous Data Lakes	2024	VLDB	0.00017267905
579	Incremental Knowledge Base Construction Using DeepDive	2015	VLDB	0.00016086569
669	CAESURA: Language Models as Multi-Modal Query Planners	2024	CIDR	0.0001495987
1,250	DB-BERT: A Database Tuning Tool that "Reads the Manual"	2022	SIGMOD	0.00011339256
1,392	Symphony: Towards Natural Language Query Answering over Multi-modal Data Lakes	2023	CIDR	0.00010807936
1,760	Structured Querying of Web Text: A Technical Challenge	2007	CIDR	9.7106555e-05
1,978	Table-GPT: Table Fine-tuned GPT for Diverse Table Tasks	2024	SIGMOD	9.2730152e-05
2,286	Join Queries with External Text Sources: Execution and Optimization Techniques	1995	SIGMOD	8.6942645e-05
2,477	A Relational Approach to Incrementally Extracting and Querying Structure in Unstructured Data	2007	VLDB	8.4079432e-05
2,521	GitTables: A Large-Scale Corpus of Relational Tables	2023	SIGMOD	8.3479333e-05
7,181	FlexER: Flexible Entity Resolution for Multiple Intents	2023	SIGMOD	5.5923113e-05
7,800	Subjective Databases	2019	VLDB	5.4507674e-05
9,549	GIO: Generating Efficient Matrix and Frame Readers for Custom Data Formats by Example	2023	SIGMOD	5.1599622e-05

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