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<span style="font-weight: 700;">_______________________________________________________________________________________</span></div>
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<span style="font-weight: 700;">WAFL 2026 – Deadline Extended</span></div>
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<span style="font-weight: 700;">4th Workshop on Advancements in Federated Learning (WAFL)</span></div>
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<span style="font-weight: 700;">Towards Trustworthy Federated Learning</span></div>
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<a href="https://wafl2026.di.unito.it/" id="OWA869f0248-bbd4-b0b6-3045-3a38e82e5c66" class="OWAAutoLink" style="color: rgb(70, 120, 134);"><u>https://wafl2026.di.unito.it/</u></a></div>
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<span style="font-weight: 700;">Co-located with ECML-PKDD 2026, Naples, Italy</span></div>
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<span style="font-weight: 700;">_______________________________________________________________________________________</span></div>
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Dear colleagues,</div>
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We are pleased to announce that the submission deadline for the 4th Workshop on Advancements in Federated Learning (WAFL 2026) has been extended to
<span style="font-weight: 700;">June 12th, 2026</span>. </div>
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We warmly invite you to submit your work and kindly encourage you to share this call with colleagues and interested researchers.</div>
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IMPORTANT DATES</div>
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• Submission deadline: <span style="font-weight: 700;">June 12th, 2026</span></div>
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• Author notification: July 1st, 2026</div>
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• Camera-ready: July 10th, 2026</div>
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• Workshop: September 11th, 2026</div>
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ABOUT THE WORKSHOP</div>
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As machine learning systems become increasingly embedded in society, concerns around privacy, fairness, robustness, and regulatory compliance continue to grow—especially under frameworks such as the GDPR and the European AI Act (2024).</div>
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Federated Learning (FL) enables collaborative model training without sharing raw data, but also raises challenges such as adversarial robustness, bias from heterogeneous data, and limited transparency.</div>
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WAFL 2026 focuses on Federated Learning, bringing together contributions addressing fairness, privacy, robustness, accountability in decentralized AI and with a major focus on trustworthiness of federated learning systems.</div>
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TOPICS OF INTEREST</div>
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• Algorithmic and theoretical advances in FL</div>
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• FL under non-IID data distributions</div>
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• Privacy and security (e.g., differential privacy, adversarial/poisoning attacks, secure aggregation)</div>
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• Fairness, interpretability, and explainability in FL</div>
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• Decentralized and peer-to-peer FL</div>
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• Transparency and accountability</div>
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• Regulatory compliance (GDPR, EU AI Act)</div>
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• Real-world applications (e.g., healthcare, finance, edge devices)</div>
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• Tools and benchmarks for FL</div>
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<span style="font-weight: 700;"> </span></div>
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<span style="font-weight: 700;">SPECIAL ISSUE</span></div>
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Selected papers will be invited to a special issue on</div>
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<span style="color: rgb(0, 0, 0); font-weight: 700;">“Trustworthy and Responsible Federated Learning”</span><span style="color: rgb(0, 0, 0);"> in
<i>Discover Artificial Intelligence</i> (Springer): </span><span style="color: rgb(70, 120, 134);"><a href="https://link.springer.com/collections/fdcjaidaif" id="OWAc354e826-fdf1-1afd-b767-493dc5478229" class="OWAAutoLink" style="color: rgb(70, 120, 134);"><u>https://link.springer.com/collections/fdcjaidaif</u></a></span></div>
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SUBMISSION DETAILS</div>
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• Long papers: 12 pages + references + supplementary</div>
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• Short papers: 6 pages + references + supplementary</div>
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• Non-archival submissions allowed</div>
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Submissions follow ECML-PKDD guidelines and will undergo double-blind review.</div>
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<span style="color: rgb(0, 0, 0);">Submission: </span><span style="color: rgb(17, 85, 204);"><a href="https://cmt3.research.microsoft.com/User/Login?ReturnUrl=%2FECMLPKDDWT2026%2FSubmission%2FIndex" id="OWA38ea2596-1533-92fc-883c-be0ea8d80f7a" class="OWAAutoLink" style="color: rgb(17, 85, 204);"><u>https://cmt3.research.microsoft.com/User/Login?ReturnUrl=%2FECMLPKDDWT2026%2FSubmission%2FIndex</u></a></span><span style="color: rgb(0, 0, 0);"> (select
WAFL track)</span></div>
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Accepted papers will be presented at the workshop and included (optional) in <span style="font-weight: 700;">
Springer CCIS proceedings</span>.</div>
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<span style="color: rgb(0, 0, 0);">For more information: </span><span style="color: rgb(70, 120, 134);"><a href="https://wafl2026.di.unito.it/" id="OWAb7975dfe-bc15-5204-88ba-e2b6fea36d16" class="OWAAutoLink" style="color: rgb(70, 120, 134);"><u>https://wafl2026.di.unito.it/</u></a></span></div>
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Contact: <u>franca.roccoditorrepadula@unina</u> <u>mirko.polato@unito.it</u> <u>roberto.esposito@unito.it</u>
<u>mfisichella@l3s.de</u></div>
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Best regards,</div>
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<span style="font-weight: 700;">WAFL 2026 Organizing Committee</span></div>
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