FILM: a Fully Learned Index for Larger-than-Memory Databases
Summary: FILM: a fully learned tree index for larger-than-memory DBs using tiny approximation models to index across memory+disk, reducing in-memory index size by orders of magnitude versus anti-caching. An adaptive LRU piggybacked on queries avoids swap overhead, improving query latency and insertion performance. (summarized by gpt-5-mini on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Chaohong Ma
- 2. Xiaohui Yu
- 3. Yifan Li
- 4. Xiaofeng Meng
- 5. Aishan Maoliniyazi
Incoming Citations (Sorted by Pagerank)
Showing 9 of 9 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 5,072 | Learned Index: A Comprehensive Experimental Evaluation | 2023 | VLDB | 5.7121108e-05 |
| 7,389 | Making In-Memory Learned Indexes Efficient on Disk | 2024 | SIGMOD | 4.7386163e-05 |
| 7,870 | SALI: A Scalable Adaptive Learned Index Framework based on Probability Models | 2023 | SIGMOD | 4.6271153e-05 |
| 8,079 | Accelerating String-key Learned Index Structures via Memoization-based Incremental Training | 2024 | VLDB | 4.5873372e-05 |
| 8,668 | Algorithmic Complexity Attacks on Dynamic Learned Indexes | 2024 | VLDB | 4.4671214e-05 |
| 9,351 | Can Learned Indexes be Built Efficiently? A Deep Dive into Sampling Trade-offs | 2024 | SIGMOD | 4.3490308e-05 |
| 10,038 | Understanding Robustness Issues of Updatable Learned Indexes: [Experiments & Analysis] | 2026 | SIGMOD | 4.1905499e-05 |
| 10,087 | High Performance or Low Memory? An Updatable Learned Index Framework for Time-Space Tradeoff | 2026 | SIGMOD | 4.1905499e-05 |
| 10,407 | VEGA: An Active-tuning Learned Index with Group-Wise Learning Granularity | 2025 | SIGMOD | 4.1905499e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 22 of 22 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
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Semantically Similar Papers
| Overall Rank | Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 4,056 | Are Updatable Learned Indexes Ready? | 2022 | VLDB | 6.4905689e-05 |
| 8,079 | Accelerating String-key Learned Index Structures via Memoization-based Incremental Training | 2024 | VLDB | 4.5873372e-05 |
| 1,365 | FITing-Tree: A Data-aware Index Structure | 2019 | SIGMOD | 0.00012379754 |
| 10,087 | High Performance or Low Memory? An Updatable Learned Index Framework for Time-Space Tradeoff | 2026 | SIGMOD | 4.1905499e-05 |
| 1,128 | An Efficient Indexing Technique for Full-Text Database Systems | 1992 | VLDB | 0.00013782361 |
| 1,464 | Learning Multi-dimensional Indexes | 2020 | SIGMOD | 0.0001184772 |
| 7,389 | Making In-Memory Learned Indexes Efficient on Disk | 2024 | SIGMOD | 4.7386163e-05 |
| 8,811 | Tuning Hierarchical Learned Indexes on Disk and Beyond | 2022 | SIGMOD | 4.4398976e-05 |
| 1,438 | Benchmarking Learned Indexes | 2021 | VLDB | 0.00011965956 |
| 5,072 | Learned Index: A Comprehensive Experimental Evaluation | 2023 | VLDB | 5.7121108e-05 |