ConANN: Conformal Approximate Nearest Neighbor Search
Summary: ConANN applies conformal risk control to IVF ANN to deliver the first distribution‑free formal guarantees on approximation error (FNR). It adaptively probes clusters per query, often reducing probes and adding negligible overhead while matching target FNR. (summarized by gpt-5-mini on Mar 13 2026)
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Authors
- 1. Sonia Horchidan (KTH Royal Institute of Technology)
- 2. Fabian Zeiher (KTH Royal Institute of Technology)
- 3. Henrik Boström (KTH Royal Institute of Technology)
- 4. Paris Carbone (KTH Royal Institute of Technology)
BibTeX Citation
@article{horchidan_vldb26,
title = {{ConANN: Conformal Approximate Nearest Neighbor Search}},
author = {Horchidan, Sonia and Zeiher, Fabian and Boström, Henrik and Carbone, Paris},
journal = {PVLDB},
series = {{VLDB} '26},
volume = {19},
number = {1},
pages = {29--42},
doi = {10.14778/3772181.3772184},
url = {https://doi.org/10.14778/3772181.3772184},
year = {2026}
}Incoming Citations (Sorted by Pagerank)
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| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 10,876 | ConRAD: Conformal Risk-Aware Neural Databases | 2026 | VLDB | 4.9793485e-05 |
| 11,031 | Interoperability in Healthcare: A Primer and New Frontiers | 2026 | VLDB | 4.9793485e-05 |
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