QStore: Quantization-Aware Compressed Model Storage
Summary: QStore losslessly co-stores low- and high-precision foundation models as the low-precision model plus compact residuals, avoiding redundant files. Lightweight decoding preserves fast access, delivering up to 2.2× storage savings and 1.8× faster loading. (summarized by gpt-5.6-luna on Jul 24 2026)
Incoming Non-self Citations Over Time
No non-self incoming citations found for this paper in this database.
Authors
- 1. Raunak Shah (University of Illinois Urbana-Champaign)
- 2. Zhaoheng Li (University of Illinois Urbana-Champaign)
- 3. Yongjoo Park (University of Illinois Urbana-Champaign)
BibTeX Citation
@article{shah_vldb26,
title = {{QStore: Quantization-Aware Compressed Model Storage}},
author = {Shah, Raunak and Li, Zhaoheng and Park, Yongjoo},
journal = {PVLDB},
series = {{VLDB} '26},
volume = {19},
number = {3},
pages = {388--398},
doi = {10.14778/3778092.3778100},
url = {https://doi.org/10.14778/3778092.3778100},
year = {2026}
}Incoming Citations (Sorted by Pagerank)
Showing 1 of 1 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 10,685 | Chipmink: Efficient Delta Identification for Massive Object Graphs | 2026 | VLDB | 5.0723324e-05 |
Previous
Page 1 / 1
Next
Outgoing Citations (Sorted by Pagerank)
Showing 10 of 10 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 643 | Materialization Optimizations for Feature Selection Workloads | 2014 | SIGMOD | 0.00015347812 |
| 1,646 | Compressed Linear Algebra for Large-Scale Machine Learning | 2016 | VLDB | 0.00010097473 |
| 3,101 | DeepSqueeze: Deep Semantic Compression for Tabular Data | 2020 | SIGMOD | 7.7356703e-05 |
| 3,282 | ALP: Adaptive Lossless floating-Point Compression | 2023 | SIGMOD | 7.5494323e-05 |
| 6,514 | Tuple-oriented Compression for Large-scale Mini-batch Stochastic Gradient Descent | 2019 | SIGMOD | 5.8412129e-05 |
| 9,143 | AirIndex: Versatile Index Tuning Through Data and Storage | 2023 | SIGMOD | 5.3003555e-05 |
| 9,182 | SIEVE: Effective Filtered Vector Search with Collection of Indexes | 2025 | VLDB | 5.2928686e-05 |
| 10,117 | ElasticNotebook: Enabling Live Migration for Computational Notebooks | 2024 | VLDB | 5.1397431e-05 |
| 10,797 | Demo of Kishu: Time-Traveling for Computational Notebooks | 2025 | SIGMOD | 5.0723324e-05 |
| 11,174 | Kishu: Time-Traveling for Computational Notebooks | 2025 | VLDB | 5.0723324e-05 |
Previous
Page 1 / 1
Next
Semantically Similar Papers
| # | Overall Rank | Paper | Year | Venue |
|---|---|---|---|---|
| 1 | 13,339 | Waiting to Decompress: The Economics of LLM-Based Compression | 2026 | CIDR |
| 2 | 6,212 | Progressive Compressed Records: Taking a Byte out of Deep Learning Data | 2021 | VLDB |
| 3 | 9,561 | Experimental Analysis of Large-scale Learnable Vector Storage Compression | 2024 | VLDB |
| 4 | 10,632 | Efficient Cooperation-Aware Key and Value Management for LLM Inference | 2026 | VLDB |
| 5 | 10,949 | QPET: A Versatile and Portable Quantity-of-Interest-Preservation Framework for Error-Bounded Lossy Compression | 2025 | VLDB |
| 6 | 9,868 | Frequency-Store: Scaling Image AI by A Column-Store for Images | 2025 | CIDR |
| 7 | 8,939 | Privacy and Accuracy-Aware AI/ML Model Deduplication | 2025 | SIGMOD |
| 8 | 4,436 | PQCache: Product Quantization-based KVCache for Long Context LLM Inference | 2025 | SIGMOD |
| 9 | 8,665 | Everything You Always Wanted to Know About Storage Compressibility of Pre-Trained ML Models but Were Afraid to Ask | 2024 | VLDB |
| 10 | 10,426 | NeurStore: Efficient In-database Deep Learning Model Management System | 2026 | SIGMOD |