Overview
The 5th Workshop on Graphs and more Complex Structures for Learning and Reasoning (GCLR) is set to take place alongside AAAI 2026. This workshop aims to explore the intricate challenges associated with modeling complex graph structures, such as hypergraphs and multilayer networks, and their applications in foundational models and trustworthy AI. The event is significant for researchers interested in advancing the understanding and application of complex systems in AI.
Background & Relevance
The field of graph-based modeling is essential in artificial intelligence, particularly in the context of complex systems. As technology evolves, the need for effective representation of intricate relationships and interactions becomes increasingly important. Complex graph structures, including knowledge graphs and multilayer networks, provide a more nuanced understanding of data, which is crucial for developing trustworthy AI systems. This workshop serves as a platform for researchers to discuss innovative approaches and methodologies in this vital area of study.
Key Details
- Event: 5th Workshop on Graphs and more Complex Structures for Learning and Reasoning (GCLR)
- Date: In conjunction with AAAI 2026
- Submission Portal: GCLR 2026 Submission
- Important Dates:
- Poster/Short/Position Paper Submission Deadline: October 15, 2025 (Pacific Time)
- Full Paper Submission Deadline: October 15, 2025 (Pacific Time)
- Paper Notification: November 5, 2025
Eligibility & Participation
The workshop invites submissions from researchers and practitioners who can contribute to the theory and applications of complex graph structures. It targets individuals interested in the intersection of graph theory and AI, particularly those working on foundational models and trustworthy AI.
Submission or Application Guidelines
Submissions are welcome in two formats:
– Poster/Short/Position Papers: These should present preliminary ideas or previously published work that can stimulate discussion. Submissions may consist of up to 4 pages, with an additional page for references.
– Full Papers: Original research that has not been published elsewhere is encouraged. These submissions can be up to 7 pages of technical content, plus two additional pages for references.
All submissions must adhere to the AAAI paper guidelines, which can be found here. Accepted papers may be published on the workshop website unless authors request otherwise.
Additional Context / Real-World Relevance
The workshop addresses critical issues in AI, particularly the need for trustworthy systems that can handle complex data structures. As AI applications increasingly rely on sophisticated models, understanding the underlying graph structures becomes essential. This event will foster collaboration and innovation among researchers working on these pressing challenges.
Conclusion
The GCLR workshop at AAAI 2026 presents a valuable opportunity for researchers to engage with peers and share insights on complex graph structures and their implications for AI. Interested participants are encouraged to submit their work and contribute to the discussions that will shape the future of this field.
Category: CFP & Deadlines
Tags: graphs, complex structures, machine learning, trustworthy ai, knowledge graphs, aaai, network analysis, causal inference
