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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 Cross-Model Consistency of Feature Importance in Electrospinning: Separating Robust from Model-Dependent Features LUCAS-MEGA: A Large-Scale Multimodal Dataset for Representation Learning in Soil-Environment Systems Inconsistent Databases and Argumentation Frameworks with Collective Attacks Workspace-Bench 1.0: Benchmarking AI Agents on Workspace Tasks with Large-Scale File Dependencies FINER-SQL: Boosting Small Language Models for Text-to-SQL Efficient Temporal Datalog Materialisation for Composite Event Recognition EGREFINE: An Execution-Grounded Optimization Framework for Text-to-SQL Schema Refinement Reliable Answers for Recurring Questions: Boosting Text-to-SQL Accuracy with Template Constrained Decoding FineState-Bench: Benchmarking State-Conditioned Grounding for Fine-grained GUI State Setting ObjectGraph: From Document Injection to Knowledge Traversal -- A Native File Format for the Agentic Era A Toolkit for Detecting Spurious Correlations in Speech Datasets SiriusHelper: An LLM Agent-Based Operations Assistant for Big Data Platforms Evergreen: Efficient Claim Verification for Semantic Aggregates CacheRAG: A Semantic Caching System for Retrieval-Augmented Generation in Knowledge Graph Question Answering Health System Scale Semantic Search Across Unstructured Clinical Notes Mining Negative Sequential Patterns to Improve Viral Genomic Feature Representation and Classification Prior-Aligned Data Cleaning for Tabular Foundation Models Spark Policy Toolkit: Semantic Contracts and Scalable Execution for Policy Learning in Spark Versioned Late Materialization for Ultra-Long Sequence Training in Recommendation Systems at Scale EPM-RL: Reinforcement Learning for On-Premise Product Mapping in E-Commerce How Hard is it to Decide if a Fact is Relevant to a Query? 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Characterizing the Program Expressive Power of Existential Rule Languages
Heng Zhang · 2021-12-15 · via cs.DB updates on arXiv.org

Existential rule languages are a family of ontology languages that have been widely used in ontology-mediated query answering (OMQA). However, for most of them, the expressive power of representing domain knowledge for OMQA, known as the program expressive power, is not well-understood yet. In this paper, we establish a number of novel characterizations for the program expressive power of several important existential rule languages, including tuple-generating dependencies (TGDs), linear TGDs, as well as disjunctive TGDs. The characterizations employ natural model-theoretic properties, and automata-theoretic properties sometimes, which thus provide powerful tools for identifying the definability of domain knowledge for OMQA in these languages.

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