Beyond Relational: Semantic-Aware Multi-Modal Analytics with LLM-Native Query Optimization
Summary: Nirvana: LLM-native semantic multi-modal analytics beyond relational operators, with programmable semantic operators and optimizer support for semantically aware query processing. Novel agentic logical optimization via NL rewrite rules + random-walk search, plus cost-aware LLM backend selection, reuse, and pushdown; strong runtime/cost gains. (summarized by gpt-5-mini on Apr 11 2026)
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Authors
- 1. Junhao Zhu (Zhejiang University)
- 2. Lu Chen (Zhejiang University)
- 3. Xiangyu Ke (Zhejiang University)
- 4. Ziquan Fang (Zhejiang University)
- 5. Tianyi Li (Aalborg University)
- 6. Yunjun Gao (Zhejiang University)
- 7. Christian S. Jensen (Aalborg University)
BibTeX Citation
@inproceedings{zhu_sigmod26,
title = {{Beyond Relational: Semantic-Aware Multi-Modal Analytics with LLM-Native Query Optimization}},
author = {Zhu, Junhao and Chen, Lu and Ke, Xiangyu and Fang, Ziquan and Li, Tianyi and Gao, Yunjun and Jensen, Christian S.},
series = {{SIGMOD} '26},
booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
publisher = {Association for Computing Machinery},
doi = {10.1145/3786628},
url = {https://dl.acm.org/doi/10.1145/3786628},
year = {2026}
}
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