Hugging Face Trending Papers
Reasoning-supported Robustness Validation of Automotive E/E Components
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arXiv AI
Aug 18
Reasoning-supported Robustness Validation of Automotive E/E Components
arXiv:2608. 16421v1 Announce Type: new Abstract: This paper presents an ontology-supported approach to tackle the complexity of the Robustness Validation (RV) process of automotive electrical/electronic (E/E) components.
arXiv AI
Jul 21
OntoExtend: A Framework for Requirement-driven and Scalable Ontology Extension with LLMs
arXiv:2607. 17963v1 Announce Type: new Abstract: Ontology extension refers to the process of enriching an existing ontology in response to emerging requirements, making it more complete.
arXiv AI
Jun 10
A Survey on Semantic Modeling for Building Energy Management
arXiv:2404. 11716v2 Announce Type: replace Abstract: Building Energy Management (BEM) is central to reducing energy use and CO2 emissions in the building sector.
arXiv AI
Sep 25
Ontology-Mediated Neurosymbolic Constraint Acquisition from Multiple Stakeholders
The paper introduces an architecture that bridges the gap between neural constraint sources and symbolic consumers by employing an OWL configuration ontology. It combines soft stakeholder preferences elicited by LLM assistants with hard hardware specifications, using description logic to detect unsatisfiability and produce symbolic explanations for interactive renegotiation. Remaining conflicts are addressed downstream through priority-based relaxation, demonstrated on a microgrid use case and positioned as broadly applicable to multi‑stakeholder domains.
arXiv AI
Aug 13
Constructing Dynamic Master Logic Models as Knowledge Graphs for Complex System Diagnostics Using Retrieval-Augmented Large Language Models
arXiv:2608. 12304v1 Announce Type: new Abstract: Dynamic Master Logic (DML) provides a hierarchical framework for representing system behavior by linking functional objectives to underlying structural elements.
arXiv AI
Jun 24
When CQs Go Wrong: Challenges in CQ Verification with OE-Assist
arXiv:2606. 24619v1 Announce Type: new Abstract: Competency Questions (CQs) are the central component of CQ-verification, an established process in which an ontology is evaluated against a set of natural language questions to determine whether the intended purpose of the ontology has been properly modelled.