[CFP] Special Track on Explainable AI–Guided Learning @ WISE 2026 – Submission Deadline: June 25, 2026

[MONCEF GAROUANI]

Dear Colleagues,

We are pleased to invite you to submit your original research contributions to the Special Track on Explainable AI–Guided Learning, co-located with the 22nd International Conference on Web Information Systems Engineering (WISE 2026).

🧠 ABOUT THE TRACK

The rapid deployment of machine learning systems in high-stakes environments has intensified the need for transparency, accountability, and interpretability. Despite their success, most deep learning and ensemble models remain inherently difficult to interpret, leading to limited trust, regulatory challenges, and reduced usability in real-world decision-making contexts. Explainable AI (XAI) has emerged as a response to this challenge, focusing primarily on post-hoc explanation methods such as feature attribution, saliency maps, or surrogate models. However, these approaches often decouple prediction and explanation, resulting in explanations that may not faithfully reflect the true reasoning of the model.

Explainable AI–Guided Learning addresses this limitation by integrating explainability directly into the learning process. Instead of explaining a model after training, explanations become part of the learning objective itself. This paradigm opens new research directions where interpretability constraints and explanation quality influence model optimization, rather than being evaluated externally. This shift enables the development of systems that are not only interpretable but also inherently designed to be explainable, bridging the gap between human cognitive processes and machine learning representations.

📌 TOPICS OF INTEREST (not limited to)

• Explainable AI-guided learning frameworks
• Interpretable and self-explaining machine learning models
• Causal inference and causal representation learning
• Explainability-driven feature selection and dimensionality reduction
• Human-in-the-loop learning with explanation feedback
• Explainable reinforcement learning
• Counterfactual and contrastive explanations for learning improvement
• Evaluation metrics for explainability-guided systems
• Trustworthy and responsible AI systems
• Applications in healthcare, education, industry, and social good
• Multimodal explainability and explainable data fusion

📅 IMPORTANT DATES

• 📤 Paper Submission Deadline: June 25, 2026
  
  
• 📬 Acceptance Notification: July 20, 2026
  
  
• 📝 Camera-Ready Deadline: August 25, 2026

⏰ All deadlines are 23:59 Anywhere on Earth (AoE).

📄 SUBMISSION GUIDELINES

•  Papers must be written in English and formatted in Springer LNCS style (up to 15 pages, including references).
  
  
• 📄 LNCS template: https://www.springer.com/gp/computer-science/lncs/conference-proceedings-guidelines
  
  
• 📮 Submission via Microsoft CMT: https://cmt3.research.microsoft.com/WISE2026
  → Select: “Special Track on Explainable AI–Guided Learning”

📚 PUBLICATION

Accepted papers will be published in the WISE 2026 proceedings, Springer LNCS series.

🌐 TRACK WEBPAGE

https://conferences.sigappfr.org/wise2026/special-track-xai-gl/

We look forward to receiving your contributions and to meeting you at WISE 2026.

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Moncef Garouani

Maître de Conférences en Informatique

Université Toulouse Capitole
Institut de Recherche en Informatique de Toulouse