First International Workshop on Generative Neuro-Symbolic AI (GeNeSy 2024) Filip Ilievski1 , Jacopo de Berardinis2 , Jongmo Kim3 and Nitisha Jain3 1 Department of Computer Science, Vrije Universiteit Amsterdam, Netherlands 2 Department of Computer Science, University of Manchester, UK 3 Department of Informatics, King’s College London, UK Abstract The fields of generative and neuro-symbolic AI have recently gained significant traction in both academia and industry, owing to their profound impact on real-world applications and their potential to achieve human-level intelligence. While generative AI excels in producing human-like outputs across various tasks, neuro-symbolic AI aims to integrate cognitive and perceptive intelligence. Despite their apparent relevance to human-level AI, the relationship between these two paradigms remains largely unexplored. The GeNeSy 2024 workshop was conceived to address this gap, providing a platform for researchers to present and discuss novel ideas and approaches in the emerging field of generative neuro-symbolic AI. Keywords Generative Model, Neuro-symbolic AI, Neuro-symbolic Representations, Large Language Models 1. Introduction The GeNeSy 2024 workshop1 sought to initiate a comprehensive discourse on the nature and definition of generative neuro-symbolic AI, encompassing its methodologies, architectures, and approaches. While Large Language Models (LLMs) undoubtedly play a central role in this domain, current research suggests that the integration of well-structured symbolic approaches—such as ontologies, knowledge graphs, and probabilistic logic programming—is crucial for developing generative models capable of human-level intelligence. Held in conjunction with the 21st Extended Semantic Web Conference (ESWC 2024) in Hersonis- sos, Greece, on May 26, 2024, the workshop benefited from the diverse expertise of attendees from both academia and industry, spanning fields such as knowledge graphs, semantic web technologies, and AI/ML. The workshop received 7 submissions, of which 6 were accepted for publication in the proceedings. These comprised 4 regular papers and 2 dissemination papers. 2. Keynotes The GeNeSy workshop featured two distinguished keynote speakers, both renowned for their significant contributions to generative neuro-symbolic AI. Sungjin Ahn2 (Professor of KAIST University) presented recent work in cognitive-grounded machine learning, opening up new opportunities to bridge both fields around common challenges. He elucidated an abstract architecture for integrating generative and inductive neural models while incorporating symbolic reasoning capabilities. Frank van Harmelen3 GeNeSy ’24: The workshop of Generative Neuro-Symboli AI, May 26–30, 2024, Hersonissos, Greece Envelope-Open f.ilievski@vu.nl (F. Ilievski); jacopo.deberardinis@kcl.ac.uk (J. d. Berardinis); jongmo.kim@kcl.ac.uk (J. Kim); nitisha.jain@kcl.ac.uk (N. Jain) GLOBE https://www.ilievski.info (F. Ilievski); http://www.jacopodeberardinis.com (J. d. Berardinis); https://nitishajain.github.io (N. Jain) Orcid 0000-0002-1735-0686 (F. Ilievski); 0000-0001-6770-1969 (J. d. Berardinis); 0000-0002-4984-1674 (J. Kim); 0000-0002-7429-7949 (N. Jain) © 2024 Copyright for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0). 1 https://sites.google.com/view/genesy2024/ 2 https://mlml.kaist.ac.kr/sungjinahn 3 https://www.cs.vu.nl/~frankh/ CEUR ceur-ws.org Workshop ISSN 1613-0073 Proceedings (Professor of Vrije University (VU) Amsterdam) delineated the crucial distinctions between neuro- symbolic and neuro-semantic AI, emphasizing the pivotal role of semantic representations in endowing neural models with comprehensive symbolic reasoning abilities. These insightful presentations have been made available on the GeNeSy website for broader dissemination and continued discussion within the research community. 3. Program Committee • Vaishak Belle, The University of Edinburgh • Inès Blin, Sony Computer Science Laboratories Paris • Jindong Jiang, Rutgers University • Ligong Han, Rutgers University • Viktor Schlegel, The University of Manchester • Jan-Christoph Kalo, University of Amsterdam • Emile van Krieken, Vrije Universiteit Amsterdam • Nicolas Lazzari, University of Bologna • Alessandro Oltramari, Bosch Research and Technology Center • Chung-Chi Chen, National Institute of Advanced Industrial Science and Technology • Pascal Hitzler, Kansas State University • Hongbo Zhu, University of Manchester • Michael Fisher, University of Manchester • Ioannis Reklos, King’s College London Acknowledgments We would like to thank all contributors, in particular the program committee, our keynote speakers, the workshop chairs of ESWC 2024, and all the authors for their contributions. Furthermore, we wish to thank the attendees of the workshop for making GeNeSy a captivating venue to discuss preliminary work in the field of generative neuro-symbolic AI.