惯性聚合 高效追踪和阅读你感兴趣的博客、新闻、科技资讯
阅读原文 在惯性聚合中打开

推荐订阅源

Blog — PlanetScale
Blog — PlanetScale
J
Java Code Geeks
月光博客
月光博客
Engineering at Meta
Engineering at Meta
WordPress大学
WordPress大学
Jina AI
Jina AI
小众软件
小众软件
U
Unit 42
云风的 BLOG
云风的 BLOG
Stack Overflow Blog
Stack Overflow Blog
雷峰网
雷峰网
博客园 - Franky
Microsoft Security Blog
Microsoft Security Blog
罗磊的独立博客
宝玉的分享
宝玉的分享
B
Blog
C
Check Point Blog
爱范儿
爱范儿
奇客Solidot–传递最新科技情报
奇客Solidot–传递最新科技情报
Cyber Security Advisories - MS-ISAC
Cyber Security Advisories - MS-ISAC
量子位
阮一峰的网络日志
阮一峰的网络日志
Vercel News
Vercel News
酷 壳 – CoolShell
酷 壳 – CoolShell

cs.DB updates on arXiv.org

Block-Sphere Vector Quantization GroupAffect-4: A Multimodal Dataset of Four-Person Collaborative Interaction CogScale: Scalable Benchmark for Sequence Processing TextAlign: Preference Alignment for Text Rendering with Hierarchical Rewards LogRouter: Adaptive Two-Level LLM Routing for Log Question Answering in Big Data Systems Agentic Cost-Aware Query Planning with Knowledge Distillation for Big Data Analytics Covariance Structure and Coordinate Heterogeneity Govern Binary Quantization of Contrastive Embeddings IVF-TQ: Calibration-Free Streaming Vector Search via a Codebook-Free Residual Layer Automatic Unsupervised Ensemble Outlier Model Selection--Extended Version A Generative AI Framework for Intelligent Utility Billing CO 2 Analytics and Sustainable Resource Optimisation Towards Foundation Models for Relational Databases with Language Models and Graph Neural Networks Gaussian Relational Graph Transformer Croissant Baker: Metadata Generation for Discoverable, Governable, and Reusable ML Datasets Reducing Hallucination in Vision-Language Models via Stage-wise Preference Optimization under Distribution Shift A Horn extension of DL-Lite with NL data complexity 3D Primitives are a Spatial Language for VLMs Enabling AI-Native Mobility in 6G: A Real-World Dataset for Handover, Beam Management, and Timing Advance A CAP-like Trilemma for Large Language Models: Correctness, Non-bias, and Utility under Semantic Underdetermination EpiCastBench: Datasets and Benchmarks for Multivariate Epidemic Forecasting FERMI: Exploiting Relations for Membership Inference Against Tabular Diffusion Models Toward Multi-Database Query Reasoning for Text2Cypher Autonomous FAIR Digital Objects: From Passive Assertions to Active Knowledge HOME-KGQA: A Benchmark Dataset for Multimodal Knowledge Graph Question Answering on Household Daily Activities Detect, Localize, and Explain: Interactive Hierarchical Log Anomaly Analytics with LLM Augmentation Open Ontologies: Tool-Augmented Ontology Engineering with Stable Matching Alignment Machine Learning-Based Pre-Test Risk Stratification for PCR-Confirmed Chlamydia Using Patient-Reported Data and Urine Biomarkers Reconciling Consistency-Based Diagnosis with Actual-Causality-Based Explanations PrepBench: How Far Are We from Natural-Language-Driven Data Preparation? Anatomy of a Query: W5H Dimensions and FAR Patterns for Text-to-SQL Evaluation Building informative materials datasets beyond targeted objectives
JSON Schema Inclusion through Refutational Normalization:...
[Submitted on 26 Mar 2026 (v1), last revised 7 Aug 2026 (this ve · 2026-03-26 · via cs.DB updates on arXiv.org

View PDF HTML (experimental)

Abstract:Deciding JSON Schema inclusion - whether every instance of a schema $S$ is also an instance of a schema $S^{\prime}$ - is a building block for version and API compatibility checks, schema refactoring, and large-scale corpus analysis. The problem is EXPTIME-complete, and the two existing families of algorithms fail in practice in complementary ways: rule-based algorithms are fast but incomplete by design, while witness-generation algorithms are complete but so slow that, under any reasonable timeout, they are incomplete in practice as well. We show that this specific problem admits a way out. We redesign the normalization core of the complete algorithm, so that, on the easy cases, it mimics the behavior of the fast rule-based algorithm, without losing completeness. We prove that it is exactly as efficient as the rule-based approach on every inclusion that approach can prove, while remaining complete on all others. We validate this on a vast collection of real-world schemas and hand-crafted schemas. We show that our algorithm advances the state of the art, making tractable a range of use cases that were out of reach for existing tools.

Submission history

From: Mohamed-Amine Baazizi [view email]
[v1] Thu, 26 Mar 2026 10:53:47 UTC (129 KB)
[v2] Mon, 13 Apr 2026 10:50:23 UTC (152 KB)
[v3] Fri, 7 Aug 2026 09:08:29 UTC (168 KB)