SemBench: A Benchmark for Semantic Query Processing Engines
Summary: SemBench benchmarks LLM-powered semantic query engines that extend SQL with natural-language operators over multimodal data. It spans diverse scenarios, modalities, and operators, exposing strengths and weaknesses across academic and industrial systems. (summarized by gpt-5.6-luna on Jul 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Jiale Lao (Cornell University)
- 2. Andreas Zimmerer (University of Technology Nuremberg)
- 3. Olga Ovcharenko (Berlin Institute for the Foundations of Learning and Data; Technical University of Berlin)
- 4. Tianji Cong (University of Michigan)
- 5. Matthew Russo (Massachusetts Institute of Technology)
- 6. Gerardo Vitagliano (Massachusetts Institute of Technology)
- 7. Michael Cochez (Vrije Universiteit Amsterdam)
- 8. Fatma Özcan (Google)
- 9. Gautam Gupta (Google)
- 10. Thibaud Hottelier (Google)
- 11. H. V. Jagadish (University of Michigan)
- 12. Kris Kissel (Google)
- 13. Sebastian Schelter (Berlin Institute for the Foundations of Learning and Data; Technical University of Berlin)
- 14. Andreas Kipf (University of Technology Nuremberg)
- 15. Immanuel Trummer (Cornell University)
BibTeX Citation
@article{lao_vldb26,
title = {{SemBench: A Benchmark for Semantic Query Processing Engines}},
author = {Lao, Jiale and Zimmerer, Andreas and Ovcharenko, Olga and Cong, Tianji and Russo, Matthew and Vitagliano, Gerardo and Cochez, Michael and Özcan, Fatma and Gupta, Gautam and Hottelier, Thibaud and Jagadish, H. V. and Kissel, Kris and Schelter, Sebastian and Kipf, Andreas and Trummer, Immanuel},
journal = {PVLDB},
series = {{VLDB} '26},
volume = {19},
number = {8},
pages = {1754--1767},
doi = {10.14778/3811243.3811249},
url = {https://doi.org/10.14778/3811243.3811249},
year = {2026}
}Incoming Citations (Sorted by Pagerank)
Showing 3 of 3 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 10,186 | Accelerating Approximate Analytical Join Queries over Unstructured Data with Statistical Guarantees | 2026 | SIGMOD | 5.093636e-05 |
| 10,190 | AgenticScholar: Agentic Data Management with Pipeline Orchestration for Scholarly Corpora | 2026 | SIGMOD | 5.093636e-05 |
| 10,501 | SQLBarber: A System Leveraging Large Language Models to Generate Customized and Realistic SQL Workloads | 2026 | SIGMOD | 5.093636e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 14 of 14 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
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