<div dir="ltr"><div style="text-align:center"><b>VINALDO: 3rd edition of International workshop on Machine vision and NLP for Document Analysis</b></div><div style="text-align:center"><strong style="border:0px;font-family:"Helvetica Neue",Helvetica,Arial,"Lucida Grande",sans-serif;font-size:13px;font-weight:bold;margin:0px;outline:0px;padding:0px;vertical-align:baseline;color:rgb(102,102,102);text-align:start;background-color:rgb(252,252,252)">Website:</strong><span style="color:rgb(102,102,102);font-family:"Helvetica Neue",Helvetica,Arial,"Lucida Grande",sans-serif;font-size:13px;text-align:start;background-color:rgb(252,252,252)"> </span><a href="https://sites.google.com/view/vinaldo3rdeditionofinternation/call-for-papers" target="_blank">https://sites.google.com/view/vinaldo3rdeditionofinternation/call-for-papers</a></div><div><br></div><div><div><p dir="ltr" style="line-height:1.55;margin-top:10.5pt;margin-bottom:0pt"><b><span style="font-family:Roboto;color:rgb(33,33,33);background-color:transparent;font-variant-numeric:normal;font-variant-east-asian:normal;font-variant-alternates:normal;vertical-align:baseline">In conjonction with <a href="https://icdar2026.org/" target="_blank">ICDAR 2026</a></span><span style="color:rgb(33,33,33);background-color:transparent;font-variant-numeric:normal;font-variant-east-asian:normal;font-variant-alternates:normal;vertical-align:baseline"> </span><span style="font-family:Roboto;color:rgb(33,33,33);background-color:transparent;font-variant-numeric:normal;font-variant-east-asian:normal;font-variant-alternates:normal;vertical-align:baseline">- Aug 30- Sep 04, 2026 • Vienna, Austria</span></b></p></div><div style="font-weight:bold"><a href="https://icdar2026.org/" target="_blank">https://icdar2026.org/</a></div><div style="font-weight:bold"><br></div><div><p dir="ltr" style="box-sizing:border-box;font-variant-ligatures:none;margin:12pt 0px 0pt;outline:none;text-decoration-line:inherit;color:rgb(33,33,33);font-size:13pt;font-family:Roboto;line-height:1.5819;background-color:transparent;border-width:initial;border-style:none;border-color:initial;padding:0pt;text-align:justify"><span style="box-sizing:border-box;color:rgb(15,17,21);font-family:Arial;font-size:11pt;vertical-align:baseline">Document understanding is essential in areas such as invoice extraction, medical record analysis, and legal document processing. While many workshops focus on pure vision-based tasks (OCR, layout analysis) or pure NLP tasks, VINALDO emphasizes the synergistic integration of computer vision and natural language processing for structured information extraction and semantic understanding of documents.</span></p><p dir="ltr" style="box-sizing:border-box;font-variant-ligatures:none;margin:0pt 0px 12pt;outline:none;text-decoration-line:inherit;color:rgb(33,33,33);font-size:13pt;font-family:Roboto;line-height:1.5819;background-color:transparent;border-width:initial;border-style:none;border-color:initial;padding:0pt;text-align:justify"><span style="box-sizing:border-box;color:rgb(15,17,21);font-family:Arial;font-size:11pt;vertical-align:baseline">This third edition of VINALDO highlights structured knowledge extraction from documents using multimodal approaches, with a focus on:</span></p><ul style="list-style-type:square;box-sizing:border-box;padding:0px;margin:6px 0px 0px;color:rgb(0,0,0);font-family:sans-serif;font-size:16px"><li dir="ltr" style="margin:0px 0px 0px 15pt;box-sizing:border-box;font-variant-ligatures:none;outline:none;text-decoration:inherit;color:rgb(33,33,33);font-size:13pt;font-style:inherit;font-weight:inherit;font-family:Roboto;line-height:1.55;padding-top:0px"><p dir="ltr" role="presentation" style="box-sizing:border-box;margin:0pt 0px 0pt 0pt;outline:none;text-decoration:inherit;font-size:13pt;font-style:inherit;font-weight:inherit;line-height:1.38;padding:0pt;background-color:transparent;border-width:initial;border-style:none;border-color:initial;text-indent:0pt"><span style="box-sizing:border-box;color:rgb(15,17,21);font-family:Arial;font-size:11pt;vertical-align:baseline">Knowledge Graphs (KGs) built from visual and textual cues</span></p></li><li dir="ltr" style="margin:6px 0px 0px 15pt;box-sizing:border-box;font-variant-ligatures:none;outline:none;text-decoration:inherit;color:rgb(33,33,33);font-size:13pt;font-style:inherit;font-weight:inherit;font-family:Roboto;line-height:1.55"><p dir="ltr" role="presentation" style="box-sizing:border-box;margin:0pt 0px 0pt 0pt;outline:none;text-decoration:inherit;font-size:13pt;font-style:inherit;font-weight:inherit;line-height:1.38;padding:0pt;background-color:transparent;border-width:initial;border-style:none;border-color:initial;text-indent:0pt"><span style="box-sizing:border-box;color:rgb(15,17,21);font-family:Arial;font-size:11pt;vertical-align:baseline">Integration of Large Language Models (LLMs) with visual document understanding</span></p></li><li dir="ltr" style="margin:6px 0px 0px 15pt;box-sizing:border-box;font-variant-ligatures:none;outline:none;text-decoration:inherit;color:rgb(33,33,33);font-size:13pt;font-style:inherit;font-weight:inherit;font-family:Roboto;line-height:1.55;padding-bottom:0px"><p dir="ltr" role="presentation" style="box-sizing:border-box;margin:0pt 0px 0pt 0pt;outline:none;text-decoration:inherit;font-size:13pt;font-style:inherit;font-weight:inherit;line-height:1.38;padding:0pt;background-color:transparent;border-width:initial;border-style:none;border-color:initial;text-indent:0pt"><span style="box-sizing:border-box;color:rgb(15,17,21);font-family:Arial;font-size:11pt;vertical-align:baseline">Multimodal representation learning for semantic retrieval</span></p></li></ul><p dir="ltr" style="box-sizing:border-box;font-variant-ligatures:none;margin:12pt 0px;outline:none;text-decoration-line:inherit;color:rgb(33,33,33);font-size:13pt;font-family:Roboto;line-height:1.5819;background-color:transparent;border-width:initial;border-style:none;border-color:initial;padding:0pt;text-align:justify"><span style="box-sizing:border-box;color:rgb(15,17,21);font-family:Arial;font-size:11pt;vertical-align:baseline">Our goal is to move beyond traditional document analysis by exploring how vision and language jointly enable structured, relational understanding particularly in complex documents like invoices, forms, and reports.</span></p><p dir="ltr" style="box-sizing:border-box;font-variant-ligatures:none;margin:15pt 0px 0pt;outline:none;text-decoration-line:inherit;color:rgb(33,33,33);font-size:13pt;font-family:Roboto;line-height:1.5819;background-color:transparent;border-width:initial;border-style:none;border-color:initial;padding:0pt;text-align:justify"><span style="box-sizing:border-box;color:rgb(0,0,0);font-family:Arial;font-size:14pt;font-style:italic;font-weight:700;vertical-align:baseline">Novelty for this edition:</span></p><p dir="ltr" style="box-sizing:border-box;font-variant-ligatures:none;margin:15pt 0px 0pt;outline:none;text-decoration-line:inherit;color:rgb(33,33,33);font-size:13pt;font-family:Roboto;line-height:1.5819;background-color:transparent;border-width:initial;border-style:none;border-color:initial;padding:0pt;text-align:justify"><span style="box-sizing:border-box;font-family:Arial;font-size:11pt;vertical-align:baseline">After the success of</span><a href="https://sites.google.com/view/vinaldo-workshop-icdar-2023/home" target="_blank" style="color:inherit;box-sizing:border-box;text-decoration-line:none"><span style="box-sizing:border-box;font-family:Arial;font-size:11pt;vertical-align:baseline"> </span><span style="box-sizing:border-box;color:rgb(17,85,204);font-family:Arial;font-size:11pt;text-decoration-line:underline;vertical-align:baseline">VINALDO 2023</span></a><span style="box-sizing:border-box;font-family:Arial;font-size:11pt;vertical-align:baseline">, and</span><a href="https://sites.google.com/view/vinaldo-workshop-icdar-2024/home" target="_blank" style="color:inherit;box-sizing:border-box;text-decoration-line:none"><span style="box-sizing:border-box;font-family:Arial;font-size:11pt;vertical-align:baseline"> </span><span style="box-sizing:border-box;color:rgb(17,85,204);font-family:Arial;font-size:11pt;text-decoration-line:underline;vertical-align:baseline">VINALDO 2024</span></a><span style="box-sizing:border-box;font-family:Arial;font-size:11pt;vertical-align:baseline">,  in </span><span style="box-sizing:border-box;color:rgb(0,0,0);font-family:Arial;font-size:11pt;vertical-align:baseline">this third edition of the VINALDO workshop, we encourage the description of novel problems or applications for document analysis in the area of information retrieval that has emerged in recent years. In the last edition</span><a href="https://sites.google.com/view/vinaldo-workshop-icdar-2024/home" target="_blank" style="color:inherit;box-sizing:border-box;text-decoration-line:none"><span style="box-sizing:border-box;color:rgb(0,0,0);font-family:Arial;font-size:11pt;vertical-align:baseline"> </span><span style="box-sizing:border-box;color:rgb(17,85,204);font-family:Arial;font-size:11pt;text-decoration-line:underline;vertical-align:baseline">VINALDO 2024</span></a><span style="box-sizing:border-box;color:rgb(0,0,0);font-family:Arial;font-size:11pt;vertical-align:baseline"> we highlighted a particular topic namely “</span><span style="box-sizing:border-box;color:rgb(0,0,0);font-family:Arial;font-size:11pt;font-weight:700;vertical-align:baseline">Knowledge Graphs and Multimodal approaches”.</span><span style="box-sizing:border-box;color:rgb(0,0,0);font-family:Arial;font-size:11pt;vertical-align:baseline"> </span></p><p dir="ltr" style="box-sizing:border-box;font-variant-ligatures:none;margin:12pt 0px;outline:none;text-decoration-line:inherit;color:rgb(33,33,33);font-size:13pt;font-family:Roboto;line-height:1.5819;background-color:transparent;border-width:initial;border-style:none;border-color:initial;padding:0pt;text-align:justify"><span style="box-sizing:border-box;font-family:Arial;font-size:11pt;vertical-align:baseline">In this new edition, we aim to encourage </span><span style="box-sizing:border-box;font-family:Arial;font-size:11pt;font-weight:700;vertical-align:baseline">novel and recent research on document analysis</span><span style="box-sizing:border-box;font-family:Arial;font-size:11pt;vertical-align:baseline"> including, but not limited to, approaches that intersect with areas such as </span><span style="box-sizing:border-box;font-family:Arial;font-size:11pt;font-weight:700;vertical-align:baseline">Large Language Models (LLMs), Knowledge Graphs (KGs), and Natural Language Processing (NLP)</span><span style="box-sizing:border-box;font-family:Arial;font-size:11pt;vertical-align:baseline">. The VINALDO workshop focuses on the </span><span style="box-sizing:border-box;font-family:Arial;font-size:11pt;font-weight:700;vertical-align:baseline">joint exploitation of visual and textual information</span><span style="box-sizing:border-box;font-family:Arial;font-size:11pt;vertical-align:baseline"> for document understanding, while remaining open to a wide range of methods and perspectives.</span></p><p dir="ltr" style="box-sizing:border-box;font-variant-ligatures:none;margin:12pt 0px;outline:none;text-decoration-line:inherit;color:rgb(33,33,33);font-size:13pt;font-family:Roboto;line-height:1.5819;background-color:transparent;border-width:initial;border-style:none;border-color:initial;padding:0pt;text-align:justify"><span style="box-sizing:border-box;font-family:Arial;font-size:11pt;vertical-align:baseline">In particular, we highlight the growing importance of </span><span style="box-sizing:border-box;font-family:Arial;font-size:11pt;font-weight:700;vertical-align:baseline">structured representations such as Knowledge Graphs extracted from document context</span><span style="box-sizing:border-box;font-family:Arial;font-size:11pt;vertical-align:baseline">, which are still underexplored despite their relevance across many application domains. We therefore welcome contributions that explore the combination of </span><span style="box-sizing:border-box;font-family:Arial;font-size:11pt;font-weight:700;vertical-align:baseline">computer vision, NLP, and structured knowledge representations</span><span style="box-sizing:border-box;font-family:Arial;font-size:11pt;vertical-align:baseline">, as well as works that integrate NLP and vision techniques in innovative ways.</span></p><p dir="ltr" style="box-sizing:border-box;font-variant-ligatures:none;margin:12pt 0px;outline:none;text-decoration-line:inherit;color:rgb(33,33,33);font-size:13pt;font-family:Roboto;line-height:1.5819;background-color:transparent;border-width:initial;border-style:none;border-color:initial;padding:0pt;text-align:justify"><span style="box-sizing:border-box;font-family:Arial;font-size:11pt;vertical-align:baseline">We also encourage submissions that introduce </span><span style="box-sizing:border-box;font-family:Arial;font-size:11pt;font-weight:700;vertical-align:baseline">new datasets, benchmarks, or real-world applications</span><span style="box-sizing:border-box;font-family:Arial;font-size:11pt;vertical-align:baseline"> related to document analysis. Overall, the VINALDO workshop aims to bring together researchers and practitioners from </span><span style="box-sizing:border-box;font-family:Arial;font-size:11pt;font-weight:700;vertical-align:baseline">academia, industry, and applied research</span><span style="box-sizing:border-box;font-family:Arial;font-size:11pt;vertical-align:baseline"> to exchange ideas, share experiences, and discuss ongoing challenges and advances in </span><span style="box-sizing:border-box;font-family:Arial;font-size:11pt;font-weight:700;vertical-align:baseline">document analysis at the intersection of Computer Vision and NLP</span></p><p dir="ltr" style="box-sizing:border-box;font-variant-ligatures:none;margin:0pt 0px;outline:none;text-decoration-line:inherit;color:rgb(33,33,33);font-size:13pt;font-family:Roboto;line-height:1.38;padding:0pt;background-color:transparent;border-width:initial;border-style:none;border-color:initial"><span style="box-sizing:border-box;color:rgb(0,0,0);font-family:Calibri,Arial;font-variant-ligatures:normal;font-variant-numeric:normal;font-variant-east-asian:normal;font-variant-alternates:normal">Researchers and practitioners all over the world, from both academia and industry, working in the areas of document and textual analysis. Topics of interest include, but are not limited to, the following:</span></p><ul style="list-style-type:square;box-sizing:border-box;padding:0px;margin:6px 0px 0px;color:rgb(0,0,0);font-family:sans-serif;font-size:16px"><li dir="ltr" style="margin:0px 0px 0px 15pt;box-sizing:border-box;font-variant-ligatures:none;outline:none;text-decoration:inherit;color:rgb(33,33,33);font-size:13pt;font-style:inherit;font-weight:inherit;font-family:Roboto;line-height:1.55;padding-top:0px"><p dir="ltr" role="presentation" style="box-sizing:border-box;margin:0pt 0px 0pt 0pt;outline:none;text-decoration:inherit;font-size:13pt;font-style:inherit;font-weight:inherit;line-height:1.38;padding:0pt;background-color:transparent;border-width:initial;border-style:none;border-color:initial;text-indent:0pt"><span style="box-sizing:border-box;color:rgb(15,17,21);font-family:Arial;font-size:11pt;vertical-align:baseline">Multimodal Knowledge Graph Construction from documents</span></p></li><li dir="ltr" style="margin:6px 0px 0px 15pt;box-sizing:border-box;font-variant-ligatures:none;outline:none;text-decoration:inherit;color:rgb(33,33,33);font-size:13pt;font-style:inherit;font-weight:inherit;font-family:Roboto;line-height:1.55"><p dir="ltr" role="presentation" style="box-sizing:border-box;margin:0pt 0px 0pt 0pt;outline:none;text-decoration:inherit;font-size:13pt;font-style:inherit;font-weight:inherit;line-height:1.38;padding:0pt;background-color:transparent;border-width:initial;border-style:none;border-color:initial;text-indent:0pt"><span style="box-sizing:border-box;color:rgb(15,17,21);font-family:Arial;font-size:11pt;vertical-align:baseline">Vision-Language Models for Document Understanding</span></p></li><li dir="ltr" style="margin:6px 0px 0px 15pt;box-sizing:border-box;font-variant-ligatures:none;outline:none;text-decoration:inherit;color:rgb(33,33,33);font-size:13pt;font-style:inherit;font-weight:inherit;font-family:Roboto;line-height:1.55"><p dir="ltr" role="presentation" style="box-sizing:border-box;margin:0pt 0px 0pt 0pt;outline:none;text-decoration:inherit;font-size:13pt;font-style:inherit;font-weight:inherit;line-height:1.38;padding:0pt;background-color:transparent;border-width:initial;border-style:none;border-color:initial;text-indent:0pt"><span style="box-sizing:border-box;color:rgb(15,17,21);font-family:Arial;font-size:11pt;vertical-align:baseline">Joint Entity and Relation Extraction from visual and textual content</span></p></li><li dir="ltr" style="margin:6px 0px 0px 15pt;box-sizing:border-box;font-variant-ligatures:none;outline:none;text-decoration:inherit;color:rgb(33,33,33);font-size:13pt;font-style:inherit;font-weight:inherit;font-family:Roboto;line-height:1.55"><p dir="ltr" role="presentation" style="box-sizing:border-box;margin:0pt 0px 0pt 0pt;outline:none;text-decoration:inherit;font-size:13pt;font-style:inherit;font-weight:inherit;line-height:1.38;padding:0pt;background-color:transparent;border-width:initial;border-style:none;border-color:initial;text-indent:0pt"><span style="box-sizing:border-box;color:rgb(15,17,21);font-family:Arial;font-size:11pt;vertical-align:baseline">Structured Document Understanding with LLMs</span></p></li><li dir="ltr" style="margin:6px 0px 0px 15pt;box-sizing:border-box;font-variant-ligatures:none;outline:none;text-decoration:inherit;color:rgb(33,33,33);font-size:13pt;font-style:inherit;font-weight:inherit;font-family:Roboto;line-height:1.55"><p dir="ltr" role="presentation" style="box-sizing:border-box;margin:0pt 0px 0pt 0pt;outline:none;text-decoration:inherit;font-size:13pt;font-style:inherit;font-weight:inherit;line-height:1.38;padding:0pt;background-color:transparent;border-width:initial;border-style:none;border-color:initial;text-indent:0pt"><span style="box-sizing:border-box;color:rgb(15,17,21);font-family:Arial;font-size:11pt;vertical-align:baseline">Multimodal Document Representation Learning</span></p></li><li dir="ltr" style="margin:6px 0px 0px 15pt;box-sizing:border-box;font-variant-ligatures:none;outline:none;text-decoration:inherit;color:rgb(33,33,33);font-size:13pt;font-style:inherit;font-weight:inherit;font-family:Roboto;line-height:1.55"><p dir="ltr" role="presentation" style="box-sizing:border-box;margin:0pt 0px 0pt 0pt;outline:none;text-decoration:inherit;font-size:13pt;font-style:inherit;font-weight:inherit;line-height:1.38;padding:0pt;background-color:transparent;border-width:initial;border-style:none;border-color:initial;text-indent:0pt"><span style="box-sizing:border-box;color:rgb(15,17,21);font-family:Arial;font-size:11pt;vertical-align:baseline">Graph-Based Spatial and Semantic Reasoning in documents</span></p></li><li dir="ltr" style="margin:6px 0px 0px 15pt;box-sizing:border-box;font-variant-ligatures:none;outline:none;text-decoration:inherit;color:rgb(33,33,33);font-size:13pt;font-style:inherit;font-weight:inherit;font-family:Roboto;line-height:1.55"><p dir="ltr" role="presentation" style="box-sizing:border-box;margin:0pt 0px 0pt 0pt;outline:none;text-decoration:inherit;font-size:13pt;font-style:inherit;font-weight:inherit;line-height:1.38;padding:0pt;background-color:transparent;border-width:initial;border-style:none;border-color:initial;text-indent:0pt"><span style="box-sizing:border-box;color:rgb(15,17,21);font-family:Arial;font-size:11pt;vertical-align:baseline">Integration of Knowledge Graphs and Vision Transformers</span></p></li><li dir="ltr" style="margin:6px 0px 0px 15pt;box-sizing:border-box;font-variant-ligatures:none;outline:none;text-decoration:inherit;color:rgb(33,33,33);font-size:13pt;font-style:inherit;font-weight:inherit;font-family:Roboto;line-height:1.55"><p dir="ltr" role="presentation" style="box-sizing:border-box;margin:0pt 0px 0pt 0pt;outline:none;text-decoration:inherit;font-size:13pt;font-style:inherit;font-weight:inherit;line-height:1.38;padding:0pt;background-color:transparent;border-width:initial;border-style:none;border-color:initial;text-indent:0pt"><span style="box-sizing:border-box;color:rgb(15,17,21);font-family:Arial;font-size:11pt;vertical-align:baseline">Multimodal Invoice and Form Analysis</span></p></li><li dir="ltr" style="margin:6px 0px 0px 15pt;box-sizing:border-box;font-variant-ligatures:none;outline:none;text-decoration:inherit;color:rgb(33,33,33);font-size:13pt;font-style:inherit;font-weight:inherit;font-family:Roboto;line-height:1.55"><p dir="ltr" role="presentation" style="box-sizing:border-box;margin:0pt 0px 0pt 0pt;outline:none;text-decoration:inherit;font-size:13pt;font-style:inherit;font-weight:inherit;line-height:1.38;padding:0pt;background-color:transparent;border-width:initial;border-style:none;border-color:initial;text-indent:0pt"><span style="box-sizing:border-box;color:rgb(15,17,21);font-family:Arial;font-size:11pt;vertical-align:baseline">Cross-modal Retrieval in Document Collections</span></p></li><li dir="ltr" style="margin:6px 0px 0px 15pt;box-sizing:border-box;font-variant-ligatures:none;outline:none;text-decoration:inherit;color:rgb(33,33,33);font-size:13pt;font-style:inherit;font-weight:inherit;font-family:Roboto;line-height:1.55;padding-bottom:0px"><p dir="ltr" role="presentation" style="box-sizing:border-box;margin:0pt 0px 0pt 0pt;outline:none;text-decoration:inherit;font-size:13pt;font-style:inherit;font-weight:inherit;line-height:1.38;padding:0pt;background-color:transparent;border-width:initial;border-style:none;border-color:initial;text-indent:0pt"><span style="box-sizing:border-box;color:rgb(15,17,21);font-family:Arial;font-size:11pt;vertical-align:baseline">Benchmarks and Datasets for Multimodal Document Understanding</span></p></li></ul><p dir="ltr" style="box-sizing:border-box;font-variant-ligatures:none;margin:12pt 0px;outline:none;text-decoration-line:inherit;color:rgb(33,33,33);font-size:13pt;font-family:Roboto;line-height:1.63645;background-color:transparent;border-width:initial;border-style:none;border-color:initial;padding:0pt;text-align:justify"><span style="box-sizing:border-box;color:rgb(15,17,21);font-family:Arial;font-size:11pt;font-style:italic;vertical-align:baseline">Note: Topics that are purely vision-based (e.g., OCR, table detection, handwriting recognition) or purely NLP-based are better suited to other ICDAR workshops. VINALDO focuses on their intersection.</span></p><p style="box-sizing:border-box;font-variant-ligatures:none;margin:12pt 0px;outline:none;text-decoration-line:inherit;color:rgb(33,33,33);font-size:13pt;font-family:Roboto;line-height:1.63645;background-color:transparent;border-width:initial;border-style:none;border-color:initial;padding:0pt;text-align:justify"><span style="box-sizing:border-box;color:rgb(15,17,21);font-family:Arial;font-size:11pt;font-style:italic;vertical-align:baseline"><b>Submission via easychair : <a href="https://easychair.org/cfp/VINALDO2026" target="_blank">https://easychair.org/cfp/VINALDO2026</a></b></span></p><p style="font-weight:bold;box-sizing:border-box;font-variant-ligatures:none;margin:12pt 0px;outline:none;color:rgb(33,33,33);font-size:13pt;font-family:Roboto;line-height:1.63645;background-color:transparent;border-width:initial;border-style:none;border-color:initial;padding:0pt;text-align:justify"><span style="box-sizing:border-box;color:rgb(15,17,21);font-family:Arial;font-size:11pt;font-style:italic;vertical-align:baseline"><u>Important Dates</u></span></p><p dir="ltr" style="font-weight:bold;box-sizing:border-box;font-variant-ligatures:none;margin:15pt 0px 0pt 36pt;outline:none;text-decoration-line:inherit;font-size:13pt;font-family:Roboto;line-height:1.44;text-indent:0pt;background-color:transparent;border-width:initial;border-style:none;border-color:initial;padding:0pt"><span style="color:rgb(0,0,0);box-sizing:border-box;font-family:Arial;font-size:11pt;vertical-align:baseline">Submission Deadline</span><span style="font-weight:400;color:rgb(0,0,0);box-sizing:border-box;font-family:Arial;font-size:11pt;vertical-align:baseline">: </span><span style="box-sizing:border-box;font-family:Arial;font-size:11pt;vertical-align:baseline"><font color="#ff0000">May 31st</font></span><span style="color:rgb(255,0,0);font-family:Arial;font-size:11pt;background-color:transparent;text-decoration-line:inherit;text-indent:0pt">, 2026 at 11:59pm AoE Time</span></p><p dir="ltr" style="box-sizing:border-box;font-variant-ligatures:none;margin:0pt 0px 0pt 36pt;outline:none;text-decoration-line:inherit;font-size:13pt;font-family:Roboto;line-height:1.44;text-indent:0pt;background-color:transparent;border-width:initial;border-style:none;border-color:initial;padding:0pt"><span style="color:rgb(0,0,0);box-sizing:border-box;font-family:Arial;font-size:11pt;font-weight:700;vertical-align:baseline">Decisions Announced</span><span style="box-sizing:border-box;font-family:Arial;font-size:11pt;vertical-align:baseline"><font color="#000000">: </font><b style=""><font color="#ff0000">June 7th, 2026, at 11:59pm AoE Time</font></b></span></p><p dir="ltr" style="box-sizing:border-box;font-variant-ligatures:none;margin:0pt 0px 0pt 36pt;outline:none;text-decoration-line:inherit;color:rgb(33,33,33);font-size:13pt;font-family:Roboto;line-height:1.44;text-indent:0pt;background-color:transparent;border-width:initial;border-style:none;border-color:initial;padding:0pt"><span style="box-sizing:border-box;color:rgb(0,0,0);font-family:Arial;font-size:11pt;font-weight:700;vertical-align:baseline">Camera Ready Deadline</span><span style="box-sizing:border-box;color:rgb(0,0,0);font-family:Arial;font-size:12pt;vertical-align:baseline">:</span><span style="box-sizing:border-box;color:rgb(0,0,0);font-family:Arial;font-size:11pt;vertical-align:baseline"> June 15th, 2026</span></p><p dir="ltr" style="box-sizing:border-box;font-variant-ligatures:none;margin:12pt 0px;outline:none;text-decoration-line:inherit;color:rgb(33,33,33);font-family:Roboto;line-height:1.63645;background-color:transparent;border-width:initial;border-style:none;border-color:initial;padding:0pt;text-align:justify"><span style="box-sizing:border-box;color:rgb(15,17,21);font-family:Arial;font-style:italic;vertical-align:baseline"><span style="font-family:Roboto,Arial;font-weight:700;color:rgb(33,33,33);text-decoration-line:inherit;text-align:left;font-style:normal">Contact:</span></span></p><p dir="ltr" style="box-sizing:border-box;font-variant-ligatures:none;margin:14px 0px 0px 0pt;outline:none;text-decoration-line:inherit;color:rgb(33,33,33);font-family:Roboto;line-height:1.55;padding-left:0pt;text-indent:15pt"><a href="mailto:rim.hantach@gmail.com" target="_blank" style="color:inherit;box-sizing:border-box;text-decoration-line:none"><span style="box-sizing:border-box;color:inherit;text-decoration-line:underline">Rim Hantach</span></a></p><p dir="ltr" style="box-sizing:border-box;font-variant-ligatures:none;margin:14px 0px 0px 0pt;outline:none;text-decoration-line:inherit;color:rgb(33,33,33);font-family:Roboto;line-height:1.55;padding-left:0pt;text-indent:15pt"><a href="mailto:boutalbi.rafika@gmail.com" target="_blank" style="color:inherit;box-sizing:border-box;text-decoration-line:none"><span style="box-sizing:border-box;color:inherit;text-decoration-line:underline">Rafika Boutalbi</span></a><span style="box-sizing:border-box"> </span></p><p dir="ltr" style="box-sizing:border-box;font-variant-ligatures:none;margin:12pt 0px;outline:none;text-decoration-line:inherit;color:rgb(33,33,33);font-family:Roboto;line-height:1.63645;background-color:transparent;border-width:initial;border-style:none;border-color:initial;padding:0pt;text-align:justify"><span style="box-sizing:border-box;color:rgb(15,17,21);font-family:Arial;font-style:italic;vertical-align:baseline"></span></p><p dir="ltr" style="box-sizing:border-box;font-variant-ligatures:none;margin:14px 0px 0px 0pt;outline:none;text-decoration-line:inherit;color:rgb(33,33,33);font-family:Roboto;line-height:1.55;padding-bottom:0px;padding-left:0pt;text-indent:15pt"><a href="mailto:karima.boutalbi1@gmail.com" target="_blank" style="color:inherit;box-sizing:border-box;text-decoration-line:none"><span style="box-sizing:border-box;color:inherit;text-decoration-line:underline">Karima Boutalbi</span></a></p></div></div></div>