CADENZA in Action: Breaking the Monolith with Intent-Dependent Plan Spaces for Semantic Queries
Summary: CADENZA compiles natural-language intents into decomposed, intent-dependent plan spaces, replacing monolithic LLM/embedding optimization. It selects and tunes physical implementations under user quality–latency–cost preferences, exposed via an interactive multimodal-data demo. (summarized by gpt-5.6-luna on Aug 28 2026)
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Authors
- 1. Jaehyun Ha (Pohang University of Science and Technology)
- 2. Yongjoo Park (University of Illinois Urbana-Champaign)
- 3. Wook-Shin Han (Pohang University of Science and Technology)
BibTeX Citation
@article{ha_vldb26,
title = {{CADENZA in Action: Breaking the Monolith with Intent-Dependent Plan Spaces for Semantic Queries}},
author = {Ha, Jaehyun and Park, Yongjoo and Han, Wook-Shin},
journal = {PVLDB},
series = {{VLDB} '26},
volume = {19},
number = {12},
pages = {4634--4637},
doi = {10.14778/3827998.3828084},
url = {https://doi.org/10.14778/3827998.3828084},
year = {2026}
}
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Outgoing Citations (Sorted by Pagerank)
Showing 7 of 7 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 683 | DocETL: Agentic Query Rewriting and Evaluation for Complex Document Processing | 2025 | VLDB | 0.00014817539 |
| 748 | Palimpzest: Optimizing AI-Powered Analytics with Declarative Query Processing | 2025 | CIDR | 0.00014281926 |
| 2,982 | Semantic Operators and Their Optimization: Enabling LLM-Based Data Processing with Accuracy Guarantees in LOTUS | 2025 | VLDB | 7.7845174e-05 |
| 3,126 | Abacus: A Cost-Based Optimizer for Semantic Operator Systems | 2026 | VLDB | 7.6185225e-05 |
| 4,142 | AOP: Automated and Interactive LLM Pipeline Orchestration for Answering Complex Queries | 2025 | CIDR | 6.7814795e-05 |
| 5,501 | SemBench: A Benchmark for Semantic Query Processing Engines | 2026 | VLDB | 6.1027188e-05 |
| 6,379 | Unify: A System For Unstructured Data Analytics | 2025 | VLDB | 5.8083127e-05 |
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