Balancing the Blend: An Experimental Analysis of Trade-offs in Hybrid Search
Summary: First systematic evaluation of hybrid retrieval across four paradigms and 11 datasets. Reveals weakest-link degradation, data/resource-dependent fusion trade-offs, and tensor-based reranking as a cost-efficient alternative. (summarized by gpt-5.6-luna on Jul 24 2026)
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Authors
- 1. Mengzhao Wang (Zhejiang University)
- 2. Boyu Tan (Zhejiang University)
- 3. Yunjun Gao (Zhejiang University)
- 4. Hai Jin (Infiniflow)
- 5. Yingfeng Zhang (Infiniflow)
- 6. Xiangyu Ke (Zhejiang University)
- 7. Xiaoliang Xu (Hangzhou Dianzi University)
- 8. Yifan Zhu (Zhejiang University)
BibTeX Citation
@article{wang_vldb26,
title = {{Balancing the Blend: An Experimental Analysis of Trade-offs in Hybrid Search}},
author = {Wang, Mengzhao and Tan, Boyu and Gao, Yunjun and Jin, Hai and Zhang, Yingfeng and Ke, Xiangyu and Xu, Xiaoliang and Zhu, Yifan},
journal = {PVLDB},
series = {{VLDB} '26},
volume = {19},
number = {8},
pages = {1715--1730},
doi = {10.14778/3811243.3811246},
url = {https://doi.org/10.14778/3811243.3811246},
year = {2026}
}
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