<!DOCTYPE html>
<html>
  <head>

    <meta http-equiv="content-type" content="text/html; charset=UTF-8">
  </head>
  <body>
    <div>
      <p dir="ltr"
        style="line-height:1.38;margin-top:0pt;margin-bottom:0pt"><span
style="font-variant-numeric:normal;font-variant-east-asian:normal;font-variant-alternates:normal;vertical-align:baseline"><font
            face="arial, sans-serif" style="color:rgb(0,0,0)">***
            Apologies for cross-postings ***</font></span></p>
      <font face="arial, sans-serif" style="color:rgb(0,0,0)"><br>
      </font>
      <p dir="ltr"
        style="line-height:1.38;margin-top:0pt;margin-bottom:0pt"><span
style="font-variant-numeric:normal;font-variant-east-asian:normal;font-variant-alternates:normal;vertical-align:baseline">XAI-KRKG<font
            face="arial, sans-serif" style="color:rgb(0,0,0)"> Workshop
            @ECAI2025 - CALL FOR PAPERS</font></span></p>
      <p dir="ltr"
        style="line-height:1.38;margin-top:0pt;margin-bottom:0pt"><span
style="font-variant-numeric:normal;font-variant-east-asian:normal;font-variant-alternates:normal;vertical-align:baseline"><font
            face="arial, sans-serif" style="color:rgb(0,0,0)">----------------------------------------------------------------------</font></span></p>
      <p dir="ltr"
        style="line-height:1.38;margin-top:0pt;margin-bottom:0pt"><span
style="font-variant-numeric:normal;font-variant-east-asian:normal;font-variant-alternates:normal;vertical-align:baseline"><font
            face="arial, sans-serif" style="color:rgb(0,0,0)">1st
            International Workshop on </font>Explainable AI, Knowledge
          Representation, and Knowledge Graphs<font
            face="arial, sans-serif" style="color:rgb(0,0,0)"> (XAI-KRKG)</font></span></p>
      <p dir="ltr"
        style="line-height:1.38;margin-top:0pt;margin-bottom:0pt"><span
style="font-variant-numeric:normal;font-variant-east-asian:normal;font-variant-alternates:normal;vertical-align:baseline"><font
            face="arial, sans-serif" style="color:rgb(0,0,0)">October
            25-26, 2025</font></span></p>
      <font face="arial, sans-serif" style="color:rgb(0,0,0)"><br>
      </font>
      <p dir="ltr"
        style="line-height:1.38;margin-top:0pt;margin-bottom:0pt"><font
          face="arial, sans-serif" style="color:rgb(0,0,0)"><span
style="font-variant-numeric:normal;font-variant-east-asian:normal;font-variant-alternates:normal;vertical-align:baseline">co-located
            with ECAI 2025 (</span></font><a
          href="https://ecai2025.org/" target="_blank"
          class="moz-txt-link-freetext">https://ecai2025.org/</a><font
          face="arial, sans-serif" style="color:rgb(0,0,0)"><span
style="font-variant-numeric:normal;font-variant-east-asian:normal;font-variant-alternates:normal;vertical-align:baseline">)
            - Bologna, Italy</span></font></p>
      <font face="arial, sans-serif" style="color:rgb(0,0,0)"><br>
      </font>
      <p dir="ltr"
        style="line-height:1.38;margin-top:0pt;margin-bottom:0pt"><font
          face="arial, sans-serif" style="color:rgb(0,0,0)"><span
style="font-variant-numeric:normal;font-variant-east-asian:normal;font-variant-alternates:normal;vertical-align:baseline">Web: </span></font><a
          href="https://sites.google.com/unical.it/xai-krkgecai/"
          target="_blank" class="moz-txt-link-freetext">https://sites.google.com/unical.it/xai-krkgecai/</a></p>
      <font face="arial, sans-serif" style="color:rgb(0,0,0)"><br>
      </font>
      <p dir="ltr"
        style="line-height:1.38;margin-top:0pt;margin-bottom:0pt"><font
          face="arial, sans-serif" style="color:rgb(0,0,0)"><span
style="font-variant-numeric:normal;font-variant-east-asian:normal;font-variant-alternates:normal;vertical-align:baseline">Submission: </span></font><a
          href="https://easychair.org/conferences?conf=xaikrkgecai2025"
          target="_blank" class="moz-txt-link-freetext">https://easychair.org/conferences?conf=xaikrkgecai2025</a></p>
      <font face="arial, sans-serif" style="color:rgb(0,0,0)"><br>
      </font>
      <p dir="ltr"
        style="line-height:1.38;margin-top:0pt;margin-bottom:0pt"><span
style="font-variant-numeric:normal;font-variant-east-asian:normal;font-variant-alternates:normal;vertical-align:baseline"><font
            face="arial, sans-serif" style="color:rgb(0,0,0)">================</font></span></p>
      <p dir="ltr"
        style="line-height:1.38;margin-top:0pt;margin-bottom:0pt"><span
style="font-variant-numeric:normal;font-variant-east-asian:normal;font-variant-alternates:normal;vertical-align:baseline"><font
            face="arial, sans-serif" style="color:rgb(0,0,0)">IMPORTANT
            DATES</font></span></p>
      <p dir="ltr"
        style="line-height:1.38;margin-top:0pt;margin-bottom:0pt"><span
style="font-variant-numeric:normal;font-variant-east-asian:normal;font-variant-alternates:normal;vertical-align:baseline"><font
            face="arial, sans-serif" style="color:rgb(0,0,0)">================</font></span></p>
      <p dir="ltr"
        style="line-height:1.38;margin-top:0pt;margin-bottom:0pt"><span
style="font-variant-numeric:normal;font-variant-east-asian:normal;font-variant-alternates:normal;vertical-align:baseline"><font
            face="arial, sans-serif" style="color:rgb(0,0,0)">Paper
            Submission Deadline: 15th May 2025 </font></span></p>
      <p dir="ltr"
        style="line-height:1.38;margin-top:0pt;margin-bottom:0pt"><span
style="font-variant-numeric:normal;font-variant-east-asian:normal;font-variant-alternates:normal;vertical-align:baseline"><font
            face="arial, sans-serif" style="color:rgb(0,0,0)">Paper
            Notification: 6th June 2025</font></span></p>
      <p dir="ltr"
        style="line-height:1.38;margin-top:0pt;margin-bottom:0pt"><span
style="font-variant-numeric:normal;font-variant-east-asian:normal;font-variant-alternates:normal;vertical-align:baseline"><font
            face="arial, sans-serif" style="color:rgb(0,0,0)">Camera
            Ready: 17th April 2025</font></span></p>
      <p dir="ltr"
        style="line-height:1.38;margin-top:0pt;margin-bottom:0pt"><span
style="font-variant-numeric:normal;font-variant-east-asian:normal;font-variant-alternates:normal;vertical-align:baseline"><font
            face="arial, sans-serif" style="color:rgb(0,0,0)">Workshop:
            25-26 October 2025 (EXACT DAY TO BE CONFIRMED)</font></span></p>
      <font face="arial, sans-serif" style="color:rgb(0,0,0)"><br>
      </font>
      <p dir="ltr"
        style="line-height:1.38;margin-top:0pt;margin-bottom:0pt"><span
style="font-variant-numeric:normal;font-variant-east-asian:normal;font-variant-alternates:normal;vertical-align:baseline"><font
            face="arial, sans-serif" style="color:rgb(0,0,0)">=========</font></span></p>
      <p dir="ltr"
        style="line-height:1.38;margin-top:0pt;margin-bottom:0pt"><span
style="font-variant-numeric:normal;font-variant-east-asian:normal;font-variant-alternates:normal;vertical-align:baseline"><font
            face="arial, sans-serif" style="color:rgb(0,0,0)">SCOPE</font></span></p>
      <p dir="ltr"
        style="line-height:1.38;margin-top:0pt;margin-bottom:0pt"><span
style="font-variant-numeric:normal;font-variant-east-asian:normal;font-variant-alternates:normal;vertical-align:baseline"><font
            face="arial, sans-serif" style="color:rgb(0,0,0)">=========</font></span></p>
      <font face="arial, sans-serif"><br>
      </font>
      <p dir="ltr"
        style="line-height:1.38;margin-top:0pt;margin-bottom:0pt">The
        integration of Explainable AI (XAI) with Knowledge
        Representation (KR) and Knowledge Graphs (KGs) has emerged as a
        critical field of study, addressing the growing need for AI
        systems that are transparent, explainable, interpretable, and
        trustworthy. Knowledge Representation offers methods for
        describing, organizing, encoding, and reasoning with
        domain-specific knowledge, providing a foundational layer for AI
        understanding. Knowledge Graphs, as a seminal result of KR,
        further enable the structuring of interconnected concepts and
        relationships, forming an intuitive framework for describing
        complex domains. KGs have been effectively used as a powerful
        tool for improving results in solving different tasks in
        multiple fields such as question answering, recommendation,
        medical decision support systems, fact-checking, semantic
        search, image classification and many others. Together, KR and
        KGs provide a natural complement to XAI techniques, empowering
        AI models to produce meaningful explanations that align with
        real-world contexts and user expectations.<br>
        As AI systems become increasingly embedded in critical domains
        such as healthcare, finance, and law, the need for interpretable
        models that offer insights into their reasoning processes has
        never been more urgent. By combining XAI with KR and KGs,
        researchers and practitioners can develop systems that bridge
        the gap between technical outputs and human comprehension. This
        integration not only enhances the clarity and relevance of
        AI-generated explanations but also supports the development of
        fairer, more accountable systems by incorporating domain
        knowledge and logic into the reasoning process.<br>
        <br>
        <br>
        This workshop seeks to explore the rich opportunities and
        challenges at the intersection of XAI, KR, and KGs. Key themes
        include leveraging structured knowledge to enhance
        explainability and interpretability, using XAI methods to refine
        and validate KR and KG models, as well as to increase
        trustworthiness of machine learning models and applying these
        combined approaches to tackle real-world problems. We invite
        contributions on theoretical advancements, innovative tools, and
        case studies that demonstrate how knowledge-driven AI can
        deliver explanations that are transparent, domain-aware, and
        user-centric. By fostering collaboration among researchers,
        industry practitioners, and domain experts, this workshop aims
        to drive forward the development of ethical and impactful AI
        systems that align with human values and societal needs.</p>
      <font face="arial, sans-serif"><br>
        <br>
      </font>
      <p dir="ltr"
        style="line-height:1.38;margin-top:0pt;margin-bottom:0pt"><span
style="font-size:11pt;font-variant-numeric:normal;font-variant-east-asian:normal;font-variant-alternates:normal;vertical-align:baseline"><font
            face="arial, sans-serif">======</font></span></p>
      <p dir="ltr"
        style="line-height:1.38;margin-top:0pt;margin-bottom:0pt"><span
style="font-size:11pt;font-variant-numeric:normal;font-variant-east-asian:normal;font-variant-alternates:normal;vertical-align:baseline"><font
            face="arial, sans-serif">TOPICS</font></span></p>
      <p dir="ltr"
        style="line-height:1.38;margin-top:0pt;margin-bottom:0pt"><span
style="font-size:11pt;font-variant-numeric:normal;font-variant-east-asian:normal;font-variant-alternates:normal;vertical-align:baseline"><font
            face="arial, sans-serif">======</font></span></p>
      <p dir="ltr"
        style="line-height:1.38;margin-top:0pt;margin-bottom:0pt"><span
style="font-size:11pt;font-variant-numeric:normal;font-variant-east-asian:normal;font-variant-alternates:normal;vertical-align:baseline"><font
            face="arial, sans-serif">The main topics include but are not
            limited to:</font></span></p>
      <p dir="ltr"
        style="line-height:1.38;margin-top:0pt;margin-bottom:0pt"></p>
      <ul>
        <li style="margin-left:15px">Techniques and best practices for
          building interpretable machine learning models intertwined
          with  Knowledge Representation (KR) and Knowledge Graphs
          (KGs).</li>
        <li style="margin-left:15px">Graph-based interpretability in
          neural networks and deep learning models.</li>
        <li style="margin-left:15px">Leveraging KR and KGs to infer
          causality and improve explanations in AI.</li>
        <li style="margin-left:15px">Enhancing reasoning capabilities in
          AI through symbolic and sub-symbolic Knowledge Representation
          (KR).</li>
        <li style="margin-left:15px">Combining traditional KR methods
          with modern XAI techniques for enhanced explainability.</li>
        <li style="margin-left:15px">Using ontologies and taxonomies to
          structure interpretable AI explanations.</li>
        <li style="margin-left:15px">Theoretical frameworks for
          explainability within KR and logic-based systems.</li>
        <li style="margin-left:15px">Explainable reasoning methods in
          rule-based and knowledge-based systems.</li>
        <li style="margin-left:15px">Explainability in dynamic and
          temporal Knowledge Graphs.</li>
        <li style="margin-left:15px">Factual and Counterfactual
          explanations for KGs.</li>
        <li style="margin-left:15px">Scalable approaches for real-time
          explainable reasoning using KR and KGs.</li>
        <li style="margin-left:15px">Evaluation protocols, metrics, and
          benchmarks for assessing the quality and clarity of KR- and
          KG-based explanations.</li>
        <li style="margin-left:15px">Cross-domain evaluation of XAI
          methods in knowledge-driven AI systems.</li>
        <li style="margin-left:15px">Interactive and adaptive
          explanation frameworks using KGs.</li>
        <li style="margin-left:15px">Personalization of explanations
          through contextual KR and user feedback.</li>
        <li style="margin-left:15px">Bias and fairness in explainable
          Knowledge Graphs and KR.</li>
        <li style="margin-left:15px">Identifying and mitigating systemic
          biases in AI explanations through KR.</li>
        <li style="margin-left:15px">Ensuring fairness in
          knowledge-driven XAI applications.</li>
        <li style="margin-left:15px">Hands-on tools and open-source
          libraries for implementing XAI and KGs in real-world settings.</li>
        <li style="margin-left:15px">Novel methodologies for integrating
          probabilistic KR with XAI.</li>
      </ul>
      <p></p>
      <font face="arial, sans-serif"><br>
      </font>
      <p dir="ltr"
        style="line-height:1.38;margin-top:0pt;margin-bottom:0pt"><span
style="font-size:11pt;font-variant-numeric:normal;font-variant-east-asian:normal;font-variant-alternates:normal;vertical-align:baseline"><font
            face="arial, sans-serif">============</font></span></p>
      <p dir="ltr"
        style="line-height:1.38;margin-top:0pt;margin-bottom:0pt"><span
style="font-size:11pt;font-variant-numeric:normal;font-variant-east-asian:normal;font-variant-alternates:normal;vertical-align:baseline"><font
            face="arial, sans-serif">SUBMISSIONS</font></span></p>
      <p dir="ltr"
        style="line-height:1.38;margin-top:0pt;margin-bottom:0pt"><span
style="font-size:11pt;font-variant-numeric:normal;font-variant-east-asian:normal;font-variant-alternates:normal;vertical-align:baseline"><font
            face="arial, sans-serif">============</font></span></p>
      <p dir="ltr"
        style="line-height:1.38;margin-top:0pt;margin-bottom:0pt"><span
style="font-size:11pt;font-variant-numeric:normal;font-variant-east-asian:normal;font-variant-alternates:normal;vertical-align:baseline"><font
            face="arial, sans-serif"><br>
          </font></span></p>
      <p dir="ltr"
        style="line-height:1.38;margin-top:0pt;margin-bottom:0pt">Submissions
        must be written in English, prepared using the new CEUR-ART
        1-column style<font face="arial, sans-serif"> <span
style="font-variant-numeric:normal;font-variant-east-asian:normal;font-variant-alternates:normal;vertical-align:baseline">(which
            you can download </span><a
            href="http://ceur-ws.org/Vol-XXX/CEURART.zip"
            target="_blank" style="text-decoration-line:none"><span
style="font-variant-numeric:normal;font-variant-east-asian:normal;font-variant-alternates:normal;text-decoration-line:underline;vertical-align:baseline">here</span></a><span
style="font-variant-numeric:normal;font-variant-east-asian:normal;font-variant-alternates:normal;vertical-align:baseline">,
            also available as an Overleaf template </span><a
href="https://www.overleaf.com/latex/templates/template-for-submissions-to-ceur-workshop-proceedings-ceur-ws-dot-org/hpvjjzhjxzjk"
            target="_blank" style="text-decoration-line:none"><span
style="font-variant-numeric:normal;font-variant-east-asian:normal;font-variant-alternates:normal;text-decoration-line:underline;vertical-align:baseline">here</span></a><span
style="font-variant-numeric:normal;font-variant-east-asian:normal;font-variant-alternates:normal;vertical-align:baseline">)</span></font>, 
        formatted in PDF, and submitted through EasyChair <span
          style="font-family:arial,sans-serif">workshop page </span><a
          href="https://easychair.org/conferences?conf=xaikrkgecai2025"
          target="_blank" class="moz-txt-link-freetext">https://easychair.org/conferences?conf=xaikrkgecai2025</a>.
        XAI+KRKG 2025 invites submissions of research, industry, and
        application contributions. There are two submission formats:</p>
      <p dir="ltr"
        style="line-height:1.38;margin-top:0pt;margin-bottom:0pt"><br>
        Regular papers (max 12 pages excluding references): must contain
        enough substance that they can be cited in other publications
        and may not have appeared before.<br>
        <br>
        Short papers (max 6 pages excluding references): results and
        ideas of interest to the XAI-KRKG audience, including position
        papers, system and application descriptions and presentations of
        preliminary results, an overview of papers accepted at another
        conference. In the latter case, extended abstracts must clearly
        state the venue where the paper has been accepted.<br>
        <br>
        All accepted papers are expected to be presented at the
        conference and at least one author of each accepted paper must
        travel to the ECAI venue in person. Submissions should be
        single-blind so the names of the authors will be visible to the
        reviewers and should be indicated on the submitted files.</p>
      <p dir="ltr"
        style="line-height:1.38;margin-top:0pt;margin-bottom:0pt"><br>
      </p>
    </div>
    <div><font face="arial, sans-serif"><br>
      </font>
      <p dir="ltr"
        style="line-height:1.38;margin-top:0pt;margin-bottom:0pt"><span
style="font-size:11pt;font-variant-numeric:normal;font-variant-east-asian:normal;font-variant-alternates:normal;vertical-align:baseline"><font
            face="arial, sans-serif">================</font></span></p>
      <p dir="ltr"
        style="line-height:1.38;margin-top:0pt;margin-bottom:0pt"><span
style="font-size:11pt;font-variant-numeric:normal;font-variant-east-asian:normal;font-variant-alternates:normal;vertical-align:baseline"><font
            face="arial, sans-serif">PROCEEDINGS AND POST-PROCEEDINGS</font></span></p>
      <p dir="ltr"
        style="line-height:1.38;margin-top:0pt;margin-bottom:0pt"><span
style="font-size:11pt;font-variant-numeric:normal;font-variant-east-asian:normal;font-variant-alternates:normal;vertical-align:baseline"><font
            face="arial, sans-serif">===============</font></span></p>
      <p dir="ltr"
        style="line-height:1.38;margin-top:0pt;margin-bottom:0pt"><span
style="font-size:11pt;font-variant-numeric:normal;font-variant-east-asian:normal;font-variant-alternates:normal;vertical-align:baseline"><font
            face="arial, sans-serif"><br>
          </font></span></p>
      <p dir="ltr"
        style="line-height:1.38;margin-top:0pt;margin-bottom:0pt"><font
          face="arial, sans-serif">Meeting the criteria, proceedings of
          XAI-KRKG 2025 are planned to be published at CEUR Workshop
          Proceedings. </font></p>
      <p dir="ltr"
        style="line-height:1.38;margin-top:0pt;margin-bottom:0pt"><font
          face="arial, sans-serif"><br>
        </font></p>
      <p dir="ltr"
        style="line-height:1.38;margin-top:0pt;margin-bottom:0pt"><span
style="font-size:11pt;font-variant-numeric:normal;font-variant-east-asian:normal;font-variant-alternates:normal;vertical-align:baseline"><font
            face="arial, sans-serif">=============</font></span></p>
      <p dir="ltr"
        style="line-height:1.38;margin-top:0pt;margin-bottom:0pt"><span
style="font-size:11pt;font-variant-numeric:normal;font-variant-east-asian:normal;font-variant-alternates:normal;vertical-align:baseline"><font
            face="arial, sans-serif">ORGANIZATION</font></span></p>
      <p dir="ltr"
        style="line-height:1.38;margin-top:0pt;margin-bottom:0pt"><span
style="font-size:11pt;font-variant-numeric:normal;font-variant-east-asian:normal;font-variant-alternates:normal;vertical-align:baseline"><font
            face="arial, sans-serif">=============</font></span></p>
      <p dir="ltr"
        style="line-height:1.38;margin-top:0pt;margin-bottom:0pt"><font
          face="arial, sans-serif"><br>
        </font></p>
      <p dir="ltr"
        style="line-height:1.38;margin-top:0pt;margin-bottom:0pt">Roberto
        Barile, University of Bari, Italy<br>
        Claudia d'Amato, University of Bari, Italy<br>
        Valeria Fionda - University of Calabria, Italy<br>
        Flavio Giorgi - Sapienza University of Rome, Italy<br>
        Antonio Ielo - University of Calabria, Italy<br>
        Ilaria Tiddi - Vrije Universiteit Amsterdam, The Netherlands<br>
        Gabriele Tolomei - Sapienza University of Rome, Italy</p>
    </div>
    <p><br>
    </p>
    <pre class="moz-signature" cols="100">-- 
Prof. Claudia d'Amato, PhD
Associate Professor
Dipartimento di Informatica - LACAM-ML Lab
Università degli Studi di Bari Aldo Moro (ITALY)
<a class="moz-txt-link-freetext" href="http://www.di.uniba.it/~cdamato/">http://www.di.uniba.it/~cdamato/</a></pre>
  </body>
</html>