Connectionists: [CFP] Graph-Based Solutions for Explainable and Efficient AI @ IEEE WCCI'26

[LUCA VIRGILI]

Dear colleagues,

we are pleased to announce the Call for Papers for the 2nd Special Session on “Graph-Based Solutions for Explainable and Efficient AI”, which will be held in conjunction with the IEEE World Congress on Computational Intelligence (WCCI 2026), June 21–26, 2026.

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Special Session Description

Recent advances in Artificial Intelligence—such as Large Language Models and Vision Transformers—have achieved remarkable performance across a wide range of tasks. However, key challenges related to explainability, efficiency, and structural understanding of these models remain largely open.

Graph-based modeling offers a powerful and unifying framework to explicitly represent relationships among data, features, and model components. By leveraging graph structures, AI systems can become more transparent, robust, efficient, and context-aware.

This special session aims to bring together researchers and practitioners working on graph-based methods for improving the interpretability, efficiency, and reasoning capabilities of modern AI systems.

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Topics of Interest (include but are not limited to):
* Graph-based explainability methods for neural networks and Transformers
* Graph-based approaches for fine-tuning and adapting Large Language Models
* Graph-driven model pruning, compression, and efficiency
* Heterogeneous and multiplex graphs for multimodal data
* Graph-based reasoning, social analysis, and decision-making frameworks
* Integration of graph structures within deep learning architectures

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Important Dates
* Paper submission deadline: January 31, 2026 (AoE)
* Author notification: March 15, 2026 (AoE)
* Camera-ready submission: April 15, 2026 (AoE)

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More Information

Special Session webpage: https://sites.google.com/view/graph-based-solutions/

We warmly encourage you to submit your latest research and to share this Call for Papers with interested colleagues.

Best regards,
The Special Session Organizers
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