[CfP] The 2nd Workshop on Knowledge Graphs and Neurosymbolic AI (KG-NeSy 2025)

(apologies for potential cross-posting)

Second CfP and deadline extension
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    KG-NeSy 2025 workshop co-located with SEMANTiCS 2025
    Date: September 3, 2025
    Venue: Vienna, Austria
    Website: https://sites.google.com/view/kgnesy2025

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** Important Dates **

- 2025-07-04 (EXTENDED): Paper submission deadline
- 2025-08-01: Notification of acceptance
- 2025-09-03: KG-NeSy Workshop @ SEMANTiCS 2025

*** Call for Papers ***

Knowledge Graphs provide a robust framework for organizing and representing large-scale knowledge in machine-readable formats. Their flexibility and scalability in capturing knowledge makes them invaluable across diverse domains, fostering seamless integration with Machine Learning techniques. This integration enhances their relevance for traditional AI applications and positions them as crucial components in the emerging field of Neurosymbolic AI. At its core, Neurosymbolic AI bridges the strengths of symbolic reasoning and neural network learning.

In the rapidly-evolving landscape of AI, this workshop aims to explore research topics in the intersection of Knowledge Graphs and Neurosymbolic AI. Neurosymbolic AI/Machine Learning techniques can be applied to construct and refine Knowledge Graphs, contributing to their ongoing evolution. Simultaneously, leveraging Knowledge Graphs for learning in Neurosymbolic AI allows intelligent systems to draw insights from structured and unstructured symbolic representations, paving the way for more informed AI models and improving interpretability and transparency in their decision-making process.

We invite papers that explore these synergies as well as any other combinations, seeking to gain a better understanding of how Knowledge Graphs and Neurosymbolic AI influence and benefit each other. Application papers are also welcome.

*** Keynote Speakers ***

We are pleased to announce that Cogan Shimizu from the Wright State University, USA, will become our Keynote speaker at the KG-NeSy Workshop!

*** Topics of Interest ***

Topics of interest include, but are not limited to:

Neurosymbolic AI for Knowledge Engineering
- Knowledge Representation and Reasoning using Deep Neural Networks
- Large-Language Models for Knowledge Engineering
- Machine Learning techniques for creating, improving, or aligning Knowledge Graphs.

Knowledge Graphs and Neurosymbolic approaches for Robust, Trustworthy and Interpretable AI
- Knowledge Graph-based approaches for improving fairness, bias mitigation, and ethical AI
- Knowledge Graphs for trustworthy Neurosymbolic AI systems
- Knowledge Graphs quality and its influence on Neurosymbolic AI systems
- Knowledge Infusion in Machine Learning algorithms
- Neurosymbolic AI for (Autonomous) Agentic Systems
- Symbolic AI methods, systems, and techniques for Explainable AI
- Using symbolic reasoning and ontologies to identify, mitigate, and explain biases in neural systems
- Utilizing Knowledge Graphs, ontologies, and other structured knowledge representations to enhance AI reliability and accountability

Application of Neurosymbolic AI and Knowledge Graphs
- Applications of Neurosymbolic AI and Knowledge Graphs in Industry
- Applications of Neurosymbolic AI in domains such as medicine, biology, IoT, security, robotics and others
- Certification, auditing, and documentation of AI systems using Knowledge Graphs and Neurosymbolic AI
- Integration of Knowledge Graphs, Neurosymbolic AI and human-machine intelligence

** Submissions **

All submissions must be written in English and adhere to the CEUR-ART style (one column). Submissions can fall in one of the following categories:

- Full papers (12-15 pages)
- Short papers (5-8 pages)
- Extended abstracts from published papers (2-4 pages)

Submit your contribution to this workshop through Easychair (https://easychair.org/conferences/?conf=kgnesy2025). Further information on the format can be found in our website (https:sites.google.com/view/kgnesy2025).

** Workshop Organizers **

- Shqiponja Ahmetaj (TU Wien)
- Fajar J. Ekaputra (WU Wien)
- Andreas Ekelhart (Universität Wien)
- Sebastian Neumaier (FH St. Pölten)


--
Dr. Fajar J. Ekaputra
Assistant Professor
Institute for Data, Process, and Knowledge Management
Vienna University of Economics and Business (WU)
W-Personal: https://juang.id

W-Group: https://semantic-systems.org