NFL: Robust Learned Index via Distribution Transformation
Summary: NFL: a two-stage learned index that first applies Numerical Normalizing Flow to transform skewed key distributions into near-uniform, then builds the index on transformed keys. Introduces After-Flow Learned Index (AFLI) for robustness, with experiments showing higher throughput and lower tail latency than state-of-the-art learned indexes on synthetic and real workloads. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Shangyu Wu (City University of Hong Kong)
- 2. Yufei Cui (City University of Hong Kong)
- 3. Jinghuan Yu (City University of Hong Kong)
- 4. Xuan Sun (City University of Hong Kong)
- 5. Tei-Wei Kuo (National Taiwan University)
- 6. Chun Jason Xue (City University of Hong Kong)
BibTeX Citation
@article{wu_vldb22,
title = {{NFL: Robust Learned Index via Distribution Transformation}},
author = {Wu, Shangyu and Cui, Yufei and Yu, Jinghuan and Sun, Xuan and Kuo, Tei-Wei and Xue, Chun Jason},
journal = {PVLDB},
series = {{VLDB} '22},
volume = {15},
number = {10},
pages = {2188--2200},
doi = {10.14778/3547305.3547322},
url = {https://doi.org/10.14778/3547305.3547322},
year = {2022}
}
Incoming Citations (Sorted by Pagerank)
Showing 14 of 14 citing papers.
Previous
Page 1 / 1
Next
Outgoing Citations (Sorted by Pagerank)
Showing 14 of 14 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
Previous
Page 1 / 1
Next
Semantically Similar Papers
| # | Overall Rank | Paper | Year | Venue |
|---|---|---|---|---|
| 1 | 10,277 | On Self-Designing Learned Indexes | 2026 | SIGMOD |
| 2 | 9,411 | Can Learned Indexes be Built Efficiently? A Deep Dive into Sampling Trade-offs | 2024 | SIGMOD |
| 3 | 10,262 | LINE: A Learned Index with Group-Enhanced Leaves and Cache-Optimized Inner Tree | 2026 | SIGMOD |
| 4 | 2,806 | Are Updatable Learned Indexes Ready? | 2022 | VLDB |
| 5 | 4,300 | DILI: A Distribution-Driven Learned Index | 2023 | VLDB |
| 6 | 9,599 | Understanding Robustness Issues of Updatable Learned Indexes: [Experiments & Analysis] | 2026 | SIGMOD |
| 7 | 10,378 | High Performance or Low Memory? An Updatable Learned Index Framework for Time-Space Tradeoff | 2026 | SIGMOD |
| 8 | 6,687 | Making In-Memory Learned Indexes Efficient on Disk | 2024 | SIGMOD |
| 9 | 3,792 | Learned Index: A Comprehensive Experimental Evaluation | 2023 | VLDB |
| 10 | 847 | Benchmarking Learned Indexes | 2021 | VLDB |