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
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 2 of 2 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 10,968 | stratum: A System Infrastructure for Massive Agent-Centric ML Workloads | 2026 | VLDB | 4.9605343e-05 |
| 11,117 | Chipmink: Efficient Delta Identification for Massive Object Graphs | 2026 | VLDB | 4.9605343e-05 |
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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 |
|---|---|---|---|---|
| 656 | Materialization Optimizations for Feature Selection Workloads | 2014 | SIGMOD | 0.00015052106 |
| 1,615 | Compressed Linear Algebra for Large-Scale Machine Learning | 2016 | VLDB | 0.00010054378 |
| 2,811 | ALP: Adaptive Lossless floating-Point Compression | 2023 | SIGMOD | 7.9587454e-05 |
| 3,151 | DeepSqueeze: Deep Semantic Compression for Tabular Data | 2020 | SIGMOD | 7.5737572e-05 |
| 6,603 | Tuple-oriented Compression for Large-scale Mini-batch Stochastic Gradient Descent | 2019 | SIGMOD | 5.7204739e-05 |
| 7,585 | SIEVE: Effective Filtered Vector Search with Collection of Indexes | 2025 | VLDB | 5.4747603e-05 |
| 8,558 | AirIndex: Versatile Index Tuning Through Data and Storage | 2023 | SIGMOD | 5.3016395e-05 |
| 10,190 | Kishu: Time-Traveling for Computational Notebooks | 2025 | VLDB | 5.052396e-05 |
| 10,312 | ElasticNotebook: Enabling Live Migration for Computational Notebooks | 2024 | VLDB | 5.0264591e-05 |
| 11,215 | Demo of Kishu: Time-Traveling for Computational Notebooks | 2025 | SIGMOD | 4.9605343e-05 |
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