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  4. Second International Workshop on Scaling Knowledge Graphs for Industry (SKGi) - LLMs meet KGs: Preface
 
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2025
Conference Paper
Title

Second International Workshop on Scaling Knowledge Graphs for Industry (SKGi) - LLMs meet KGs: Preface

Abstract
This version explores the intersection of Knowledge Graphs (KGs) and Large Language Models (LLMs) with a focus on enabling scalable, efficient, and trustworthy AI applications in industrial contexts. As generative AI rapidly evolves, integrating symbolic and neural methods becomes essential to address challenges such as explainability, data alignment, and system robustness by gathering academic researchers and industry practitioners to discuss practical solutions and future of Semantic Web technologies in the era of foundation models.
Author(s)
Rincon-Yanez, Diego
Trinity College Dublin
Schmidt, Wilma Johanna
Robert Bosch GmbH
Kharlamov, Evgeny
Robert Bosch GmbH
Cochez, Michael
Vrije Universiteit Amsterdam
Paschke, Adrian  
Fraunhofer-Institut für Offene Kommunikationssysteme FOKUS  
O'Sullivan, Declan
Trinity College Dublin
Mainwork
Ceur Workshop Proceedings
Funder
ADAPT - Centre for Digital Content Technology
Conference
Joint of Posters, Demos, Workshops, and Tutorials of the 21st International Conference on Semantic Systems, SEMANTiCS-PDWT 2025
Language
English
Fraunhofer-Institut für Offene Kommunikationssysteme FOKUS  
Keyword(s)
  • AI for Industry

  • Graph Retrieval Augmented Generation

  • Knowledge Graphs

  • Large Language Models

  • Scalable AI

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