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<p class="MsoNormal"><span lang="EN-GB">We invite researchers working on interpretability and explainability in machine learning and artificial intelligence, as well as related topics, to submit regular papers (14 pages, single column) or short papers (7 pages,
single column) to the AIMLAI Workshop, to be held in conjunction with ECML/PKDD 2025.</span><span lang="EN-GB" style="font-size:12.0pt;mso-fareast-language:FR-BE"><o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-GB"><o:p> </o:p></span></p>
<p class="MsoNormal"><b><span lang="EN-GB">Website:</span></b><span lang="EN-GB"> </span><a href="https://project.inria.fr/aimlai/"><span lang="EN-GB">https://project.inria.fr/aimlai/</span></a><span lang="EN-GB"><o:p></o:p></span></p>
<p class="MsoNormal"><b><span lang="EN-GB">Submission link: </span></b><a href="https://cmt3.research.microsoft.com/ECMLPKDDWorkshopTrack2025/Submission/Index"><span lang="EN-GB">https://cmt3.research.microsoft.com/ECMLPKDDWorkshopTrack2025/Submission/Index</span></a><span lang="EN-GB"><o:p></o:p></span></p>
<p class="MsoNormal"><b><span lang="EN-GB">Submission deadline:</span></b><span lang="EN-GB"> June 14, 2025<o:p></o:p></span></p>
<p class="MsoNormal"><b><span lang="EN-GB">Workshop: </span></b><span lang="EN-GB">September 15, 2025<o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-GB"><o:p> </o:p></span></p>
<p class="MsoNormal"><span lang="EN-GB">AIMLAI (Advances in Interpretable Machine Learning and Artificial Intelligence) aims to foster principled research and discussion on building explainable machine learning and AI systems . We invite contributions from
researchers in academia and industry that approach the challenges of achieving explainability and interpretability in AI systems from technical, as well as legal, ethical, or sociological perspectives.<o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-GB"><o:p> </o:p></span></p>
<p class="MsoNormal"><b><span lang="EN-GB">Submissions may include:</span></b><span lang="EN-GB"><o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-GB">• Novel research results<o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-GB">• Application experiences<o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-GB">• Tools and systems<o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-GB">• Preliminary ideas with promising potential<o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-GB"><o:p> </o:p></span></p>
<p class="MsoNormal"><b><span lang="EN-GB">Topics of Interest (non-exhaustive)</span></b><span lang="EN-GB"><o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-GB">Interpretable Machine Learning<o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-GB">• Interpretable-by-design models<o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-GB">• Explainable recommendation systems<o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-GB">• Multimodal explanations<o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-GB">• Explainability for large language models (LLMs)<o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-GB">• LLMs as tools for explainability<o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-GB">• Mechanistic interpretability<o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-GB"><o:p> </o:p></span></p>
<p class="MsoNormal"><span lang="EN-GB">Transparency, Ethics, Fairness and Privacy<o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-GB">• Ethical implications of AI/ML<o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-GB">• Legal frameworks and compliance<o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-GB">• Fairness and bias mitigation<o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-GB">• Interplay of explainability and privacy
<o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-GB"><o:p> </o:p></span></p>
<p class="MsoNormal"><span lang="EN-GB">Methodology & Evaluation<o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-GB">• Formal measures of interpretability and explainability<o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-GB">• Trade-offs between interpretability and model complexity<o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-GB">• Evaluation frameworks<o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-GB">• User-centered interpretability<o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-GB"> Explanation Modules & Human Integration<o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-GB">• Semantics in explanations<o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-GB">• Human-in-the-loop systems<o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-GB">• Combining ML, information visualization, and human-computer interaction<o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-GB"><o:p> </o:p></span></p>
<p class="MsoNormal"><span lang="EN-GB">We look forward to your contributions and to engaging discussions at AIMLAI 2025!<o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-GB"><o:p> </o:p></span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span>Tassadit Bouadi (University of Rennes/IRISA, France)<o:p></o:p></p>
<p class="MsoNormal"> <span lang="EN-GB">Benoît Frénay (University of Namur, Belgium)<o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span>Luis Galárraga (Inria/IRISA, France)<o:p></o:p></p>
<p class="MsoNormal"> <span lang="EN-GB">Megha Khosla (TU Delft)<o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-GB"> José Oramas (University of Antwerp/imec-IDLab, Belgium)<o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-GB"><o:p> </o:p></span></p>
<p class="MsoNormal" style="margin:12.0pt"><b><span lang="EN-GB" style="font-size:8.0pt;font-family:"Verdana",sans-serif;color:#616365;mso-ligatures:standardcontextual;mso-fareast-language:FR-BE">Benoît Frénay</span></b><span lang="EN-GB" style="font-size:8.0pt;font-family:"Verdana",sans-serif;color:#616365;mso-ligatures:standardcontextual;mso-fareast-language:FR-BE"><br>
</span><span lang="EN-GB" style="font-size:8.0pt;font-family:"Verdana",sans-serif;color:#69BE28;mso-ligatures:standardcontextual;mso-fareast-language:FR-BE">Professor</span><span lang="EN-GB" style="font-size:8.0pt;font-family:"Verdana",sans-serif;color:#616365;mso-ligatures:standardcontextual;mso-fareast-language:FR-BE"><br>
Faculty of Computer Science <br>
Human-Center Machine Learning (HuMaLearn)<br>
UNamur / NaDI / PReCISE<o:p></o:p></span></p>
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