QStore: Quantization-Aware Compressed Model Storage

Summary: Introduces QStore, a quantization-aware lossless format that stores a low-precision model plus compact residuals to reconstruct high-precision variants, avoiding duplicate files. Achieves up to 2.2× storage reduction and faster save/load (≈1.7–1.8×) via lightweight decoding. (summarized by gpt-5-mini on Mar 13 2026)

Paper ID: 14326
Venue: VLDB
Year: 2026
Pagerank: 4.1945683e-05
Overall Rank: 10,286 | 28.45%
DOI: 10.14778/3778092.3778100

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Incoming Citations (Sorted by Pagerank)

Showing 1 of 1 citing papers.

Rank	Citing Paper	Year	Venue	Pagerank
10,302	Chipmink: Efficient Delta Identification for Massive Object Graphs	2026	VLDB	4.1945683e-05

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
761	Materialization Optimizations for Feature Selection Workloads	2014	SIGMOD	0.00017053783
1,967	Compressed Linear Algebra for Large-Scale Machine Learning	2016	VLDB	9.9131712e-05
3,745	DeepSqueeze: Deep Semantic Compression for Tabular Data	2020	SIGMOD	6.7926132e-05
4,507	ALP: Adaptive Lossless floating-Point Compression	2023	SIGMOD	6.131017e-05
6,538	Tuple-oriented Compression for Large-scale Mini-batch Stochastic Gradient Descent	2019	SIGMOD	5.023239e-05
9,095	AirIndex: Versatile Index Tuning Through Data and Storage	2023	SIGMOD	4.3975034e-05
9,912	ElasticNotebook: Enabling Live Migration for Computational Notebooks	2024	VLDB	4.2565279e-05
10,434	Demo of Kishu: Time-Traveling for Computational Notebooks	2025	SIGMOD	4.1945683e-05
10,761	SIEVE: Effective Filtered Vector Search with Collection of Indexes	2025	VLDB	4.1945683e-05
10,888	Kishu: Time-Traveling for Computational Notebooks	2025	VLDB	4.1945683e-05

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