CGIF: Combining Proximity Graphs and Inverted Files for Efficient Filtered Vector Search over Arbitrary Predicates
Summary: CGIF augments HNSW with predicate-aware local exploration, replacing filtered-out neighbors using inverted-file candidates while preserving graph navigation. It supports arbitrary predicates and selectivities, achieving up to 2× faster filtered ANNS with high recall. (summarized by gpt-5.6-luna on Aug 28 2026)
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Authors
- 1. Jiarui Luo (Rutgers University)
- 2. Chaoji Zuo (Rutgers University)
- 3. Dong Deng (Rutgers University)
BibTeX Citation
@article{luo_vldb26,
title = {{CGIF: Combining Proximity Graphs and Inverted Files for Efficient Filtered Vector Search over Arbitrary Predicates}},
author = {Luo, Jiarui and Zuo, Chaoji and Deng, Dong},
journal = {PVLDB},
series = {{VLDB} '26},
volume = {19},
number = {11},
pages = {3663--3675},
doi = {10.14778/3836663.3836716},
url = {https://doi.org/10.14778/3836663.3836716},
year = {2026}
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Outgoing Citations (Sorted by Pagerank)
Showing 8 of 8 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 345 | A Comprehensive Survey and Experimental Comparison of Graph-Based Approximate Nearest Neighbor Search | 2021 | VLDB | 0.00020445545 |
| 1,225 | ACORN: Performant and Predicate-Agnostic Search Over Vector Embeddings and Structured Data | 2024 | SIGMOD | 0.00011444398 |
| 1,957 | SeRF: Segment Graph for Range-Filtering Approximate Nearest Neighbor Search | 2024 | SIGMOD | 9.3159589e-05 |
| 2,726 | iRangeGraph: Improvising Range-dedicated Graphs for Range-filtering Nearest Neighbor Search | 2024 | SIGMOD | 8.0904995e-05 |
| 2,783 | Navigating Labels and Vectors: A Unified Approach to Filtered Approximate Nearest Neighbor Search | 2024 | SIGMOD | 8.0242863e-05 |
| 4,346 | UNIFY: Unified Index for Range Filtered Approximate Nearest Neighbors Search | 2025 | VLDB | 6.6488514e-05 |
| 6,184 | NaviX: A Native Vector Index Design for Graph DBMSs With Robust Predicate-Agnostic Search Performance | 2025 | VLDB | 5.8586024e-05 |
| 6,768 | Dynamic Range-Filtering Approximate Nearest Neighbor Search | 2025 | VLDB | 5.686858e-05 |
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