The rapid development and deployment of Large-Language Models (LLMs) has led to growing interest in leveraging ontologies and knowledge graphs to enhance LLM capabilities and address limitations. Combining the semantically rich architectures provided by ontologies and knowledge graphs with the generative strengths of LLMs promises to provide a path towards more explainable artificial intelligence systems, more trustworthy output, and a deeper understanding of vulnerabilities arising from integrated architectures. This workshop, associated with a special issue of Applied Ontology, is dedicated to exploring the convergence of knowledge representation and LLM strategies, design patterns, models, and benchmarks. We aim to bring together researchers, practitioners, and enthusiasts from industry, academia, and government in the interest of exploring possible convergence points and advancing each field.
We invite submissions for our workshop focusing on the intersection of Applied Ontology and Large Language Models as part of FOIS 2024.
30 minutes for each talk (20m presentation + 10m Q&A)
We encourage two types of contributions:
It is our intent that full research articles submitted to this workshop will be considered for inclusion in the special issue of Applied Ontology focused on Large-Language Models and ontologies, and that some contributors to the special issue will be invited to present during this workshop.
Papers for the conference should be submitted non-anonymously in PDF format in compliance with the new 1-column CEUR-ART Style, which can be found here.
The EasyChair submission page can be found here. Be sure to select the "JOWO Workshop - Workshop on the Convergence of Large Language Models and Ontologies" track.
All contributions to JOWO workshops will be published in a joint CEUR proceedings volume, compare:
Join us in shaping the future of knowledge representation and language understanding by contributing to this cutting-edge workshop. If you have any questions regarding the preceding information please email johnbeve@buffalo.edu.