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20192026
most citedRetrieval-Augmented Generation of Ontologies from Relational Databases

1 citations · 1 across the 11 of their papers we have counts for

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cs.DB2026

Causal Explanations for Stratified Datalog

Ratan Bahadur Thapa, Steffen Staab

Rule-based reasoning with exceptions requires causal explanations that account for both present and absent facts. For positive Datalog, monotonicity allows minimal supports to dete…

cs.DB2026

Causality and Minimal Supports in Recursive Datalog

Ratan Bahadur Thapa, Steffen Staab

Explaining an inferred fact under rule evaluation can require identifying the inclusion-minimal input sets that suffice for the inference and the deletions that make the fact disap…

cs.DB2026

Identifiability of Relational Queries in Multi-View Pretraining

Ratan Bahadur Thapa, Daniel Hernández

When data sources are integrated through a shared interface, a downstream query may or may not be determined by what the interface exposes: two globally consistent worlds can agree…

cs.DB2026

On the Semantics of Generative SPARQL

Ratan Bahadur Thapa, Steffen Staab

We extend SPARQL with a generative query construct, called \tx{GenOp}, whose evaluation calls a language model and produces typed solution mappings. We define the semantics of the…

cs.DB2026

Towards Foundation Models for Relational Databases with Language Models and Graph Neural Networks

Jingcheng Wu, Ratan Bahadur Thapa, Mojtaba Nayyeri +4

Relational databases store much of the world's structured information, and they are essential for driving complex predictive applications. However, deep learning progress on relati…

cs.DB2025★ 1 cited

Retrieval-Augmented Generation of Ontologies from Relational Databases

Nadeen Fathallah, Mojtaba Nayyeri, Athish A Yogi +4

Deriving OWL ontologies from relational database schemas supports semantic interoperability and downstream tasks such as knowledge graph population, ontology-based data access, gra…