# LIRA: A Learning-based Query-aware Partition Framework for Large-scale ANN Search

arXiv: https://arxiv.org/abs/2503.23409 · HTML: https://mlsanity.com/paper/2503.23409/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 30 Mar 2025.

## Built on by (most cited first, 3 of 3)

- [The Hybrid Multimodal Graph Index (HMGI): A Comprehensive Framework for Integrated Relational and Vector Search](https://mlsanity.com/paper/2510.10123/) (2025)
- [Efficient K-generalizable Learned Search](https://mlsanity.com/paper/2603.06159/) (2026)
- [The Virtuous Cycle: AI-Powered Vector Search and Vector Search-Augmented AI](https://mlsanity.com/paper/2603.09347/) (2026)

## Abstract (arXiv)

Approximate nearest neighbor search is fundamental in information retrieval. Previous partition-based methods enhance search efficiency by probing partial partitions, yet they face two common issues. In the query phase, a common strategy is to probe partitions based on the distance ranks of a query to partition centroids, which inevitably probes irrelevant partitions as it ignores data distribution. In the partition construction phase, all partition-based methods face the boundary problem that separates a query's nearest neighbors to multiple partitions, resulting in a long-tailed kNN distribution and degrading the optimal nprobe (i.e., the number of probing partitions). To address this gap, we propose LIRA, a LearnIng-based queRy-aware pArtition framework. Specifically, we propose a probing model to directly probe the partitions containing the kNN of a query, which can reduce probing waste and allow for query-aware probing with nprobe individually. Moreover, we incorporate the probing model into a learning-based redundancy strategy to mitigate the adverse impact of the long-tailed kNN distribution on search efficiency. Extensive experiments on real-world vector datasets demonstrate the superiority of LIRA in the trade-off among accuracy, latency, and query fan-out. The codes are available at https://github.com/SimoneZeng/LIRA-ANN-search.