Rethinking Query Optimization for Multi-Agent Systems
Summary: NOMA treats agentic data pipelines as a new query-optimization problem: jointly selecting topology, LLMs, and engines across cost, latency, and accuracy despite heterogeneous data models. Its iterative loop combines plan generation, estimation, runtime refinement, and semantic caching; experiments expose large gains from non-obvious configurations. (summarized by gpt-6-luna on Oct 08 2026)
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Authors
- 1. Zoi Kaoudi (IT University of Copenhagen)
- 2. Ioana Giurgiu (International Business Machines Research Europe)
BibTeX Citation
@article{kaoudi_vldb27,
title = {{Rethinking Query Optimization for Multi-Agent Systems}},
author = {Kaoudi, Zoi and Giurgiu, Ioana},
journal = {PVLDB},
series = {{VLDB} '27},
volume = {20},
number = {1},
pages = {46--52},
doi = {10.14778/3845598.3845602},
url = {https://doi.org/10.14778/3845598.3845602},
year = {2027}
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