Detect, Distill and Update: Learned DB Systems Facing Out of Distribution Data
Summary: DDUp is an updatability framework for learned DB components facing insertion-driven shifts, pairing OOD detection with efficient updates. It uses a test to flag OOD data and a distillation-based update to keep AQP, CE, DG accurate without retraining. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
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Incoming Citations (Sorted by Pagerank)
Showing 9 of 9 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 5,941 | Eraser: Eliminating Performance Regression on Learned Query Optimizer | 2024 | VLDB | 5.2594013e-05 |
| 7,564 | Modeling Shifting Workloads for Learned Database Systems | 2024 | SIGMOD | 4.7049893e-05 |
| 7,676 | E2ETune: End-to-End Knob Tuning via Fine-tuned Generative Language Model | 2025 | VLDB | 4.6770108e-05 |
| 8,365 | NeurDB: On the Design and Implementation of an AI-powered Autonomous Database | 2025 | CIDR | 4.5305127e-05 |
| 9,215 | PACE: Poisoning Attacks on Learned Cardinality Estimation | 2024 | SIGMOD | 4.3679174e-05 |
| 9,841 | Machine Unlearning in Learned Databases: An Experimental Analysis | 2024 | SIGMOD | 4.2685233e-05 |
| 10,032 | Rainbow: Risk-aware Index Benefit Estimation Facing Out Of Distribution Workloads | 2026 | SIGMOD | 4.1905499e-05 |
| 10,038 | Understanding Robustness Issues of Updatable Learned Indexes: [Experiments & Analysis] | 2026 | SIGMOD | 4.1905499e-05 |
| 10,300 | TATA: An Efficient Framework for Task Transfer in Query Plan Representation | 2026 | VLDB | 4.1905499e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 27 of 27 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 |
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| 3,144 | Active Learning for ML Enhanced Database Systems | 2020 | SIGMOD | 7.4844943e-05 |
| 4,413 | Robust Query Driven Cardinality Estimation under Changing Workloads | 2023 | VLDB | 6.1989918e-05 |
| 2,364 | Deep Learning Models for Selectivity Estimation of Multi-Attribute Queries | 2020 | SIGMOD | 8.955077e-05 |
| 7,611 | Learning to be a Statistician: Learned Estimator for Number of Distinct Values | 2022 | VLDB | 4.6920008e-05 |
| 7,564 | Modeling Shifting Workloads for Learned Database Systems | 2024 | SIGMOD | 4.7049893e-05 |
| 1,699 | Are We Ready For Learned Cardinality Estimation? | 2021 | VLDB | 0.00010848882 |
| 5,799 | Learned Approximate Query Processing: Make it Light, Accurate and Fast | 2021 | CIDR | 5.3219666e-05 |
| 4,431 | Lightweight and Accurate Cardinality Estimation by Neural Network Gaussian Process | 2022 | SIGMOD | 6.1870601e-05 |
| 606 | DeepDB: Learn from Data, not from Queries! | 2020 | VLDB | 0.00019251186 |
| 9,841 | Machine Unlearning in Learned Databases: An Experimental Analysis | 2024 | SIGMOD | 4.2685233e-05 |