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The pervasive diffusion of Large Language Models (LLMs) requires important efforts to ensure fairness and representativity towards all social and cultural groups, potentially considering different identities that characterize potential end-users of these technologies. This special issue welcomes contributions on the development of graph-based abstractions and hybrid neuro-symbolic approaches for human-centered AI. --- Topics of Interest We solicit research, resource, and survey articles aligned with the scope of TGDK, covering (but not limited to): Ontology modeling and knowledge representation for Human-Centric AI - Knowledge representation for reducing bias in AI - Ontologies of identity dimensions and psychology for AI - Ontologies of sociological and communication theories for AI - Linked Data approaches for Human-Centric AI Data quality, integration and provenance for Human-Centric AI - FAIR and CARE principles for AI models - Graph-based provenance approaches for AI models - Incorporating cultural metadata into AI workflows - KG-driven approaches for bias detection and mitigation in archives LLM integration with graph-structured knowledge for fair AI - Question answering with LLMs and graph-structured knowledge - Reducing LLM hallucinations with graph-structured knowledge - Retrieval-Augmented Generation using graph-structured knowledge - Enhancing graph-structured knowledge using LLMs Logic and reasoning for Explainable AI - Logic-based methods for governance, ethical frameworks, and legal compliance of AI - Extraction of logic-based representations for explainable AI - Graph-based constraint languages for explainable AI --- Extended Versions of Conference Papers We explicitly welcome extended versions of previously published conference papers. If you have recently presented relevant work at a conference (e.g., NeSy, ISWC, ESWC, AAAI, IJCAI, ACL or similar venues), we strongly encourage you to consider submitting an extended version to this Special Issue. Extended versions must: - Clearly state in the introduction that the submission is an extension of a prior conference paper, with an explicit reference to it; - Clarify the novel contributions presented in the extension; - Include a significant additional contribution — such as new experiments providing stronger evidence for existing claims, new theoretical results (theorems, full proofs), or substantial new developments validating new claims. There is no fixed minimum percentage of new content, but the extension should represent a meaningful scientific advance beyond the conference version. Authors should also ensure compliance with any copyright agreements signed with the original venue — in particular, text from papers for which copyright has been transferred to another publisher should not be reused verbatim (though scientific content can, of course, be built upon). --- Submission Types - Research Articles - Survey Articles - Resource Articles (benchmarks, datasets, ontologies, tools, knowledge graphs, etc.) Expected length: 10–20 pages using the TGDK single-column LaTeX template (https://drops.dagstuhl.de/entities/journal/TGDK#author). --- 📅 Important Dates - Submission deadline: June 30, 2026 - Author notification: September 30, 2026 - Revisions: October 31, 2026 - Final notification: November 30, 2026 --- Submission Please follow the TGDK submission instructions and select this Special Issue in the submission portal: https://journal-submission.dagstuhl.de/TGDK/ Full call details are available at: https://drops.dagstuhl.de/entities/journal/TGDK#cfp-si-neuro-symbolic-modeling-for-human-centric-ai --- Guest Editors - Stefano De Giorgis, Vrije Universiteit Amsterdam, Netherlands - Marco Antonio Stranisci, University of Turin, Italy - Luana Bulla, University of Bologna, Italy - Lia Draetta, University of Turin, Italy - Rossana Damiano, University of Turin, Italy - Filip Ilievski, Vrije Universiteit Amsterdam, Netherlands We look forward to your contributions! Best regards, The Guest Editors4c:T4ab, We explicitly welcome extended versions of previously published conference papers. If you have recently presented relevant work at a conference (e.g., NeSy, ISWC, ESWC, AAAI, IJCAI, ACL or similar venues), we strongly encourage you to consider submitting an extended version to this Special Issue. Extended versions must: - Clearly state in the introduction that the submission is an extension of a prior conference paper, with an explicit reference to it; - Clarify the novel contributions presented in the extension; - Include a significant additional contribution — such as new experiments providing stronger evidence for existing claims, new theoretical results (theorems, full proofs), or substantial new developments validating new claims. There is no fixed minimum percentage of new content, but the extension should represent a meaningful scientific advance beyond the conference version. Authors should also ensure compliance with any copyright agreements signed with the original venue — in particular, text from papers for which copyright has been transferred to another publisher should not be reused verbatim (though scientific content can, of course, be built upon). --- 4d:T12f5,:mega: [CfP] TGDK Special Issue: Neuro-Symbolic Modeling for Human-Centric AI — Submission Deadline: June 30, 2026 Dear Colleagues, We are pleased to invite you to submit your work to the Special Issue on **, published in the __ — a Diamond Open Access journal by Dagstuhl Publishing (free for both authors and readers). --- *Motivation* The alignment of AI technologies with people's behaviors and worldviews has become a central challenge across many sectors of Computer Science. The pervasive diffusion of Large Language Models (LLMs) requires important efforts to ensure fairness and representativity towards all social and cultural groups, potentially considering different identities that characterize potential end-users of these technologies. This special issue welcomes contributions on the development of graph-based abstractions and hybrid neuro-symbolic approaches for human-centered AI. --- *Topics of Interest* We solicit research, resource, and survey articles aligned with the scope of TGDK, covering (but not limited to): *Ontology modeling and knowledge representation for Human-Centric AI* - Knowledge representation for reducing bias in AI - Ontologies of identity dimensions and psychology for AI - Ontologies of sociological and communication theories for AI - Linked Data approaches for Human-Centric AI *Data quality, integration and provenance for Human-Centric AI* - FAIR and CARE principles for AI models - Graph-based provenance approaches for AI models - Incorporating cultural metadata into AI workflows - KG-driven approaches for bias detection and mitigation in archives *LLM integration with graph-structured knowledge for fair AI* - Question answering with LLMs and graph-structured knowledge - Reducing LLM hallucinations with graph-structured knowledge - Retrieval-Augmented Generation using graph-structured knowledge - Enhancing graph-structured knowledge using LLMs *Logic and reasoning for Explainable AI* - Logic-based methods for governance, ethical frameworks, and legal compliance of AI - Extraction of logic-based representations for explainable AI - Graph-based constraint languages for explainable AI --- *Extended Versions of Conference Papers* We explicitly welcome extended versions of previously published conference papers. If you have recently presented relevant work at a conference (e.g., NeSy, ISWC, ESWC, AAAI, IJCAI, ACL or similar venues), we strongly encourage you to consider submitting an extended version to this Special Issue. Extended versions must: - Clearly state in the introduction that the submission is an extension of a prior conference paper, with an explicit reference to it; - Clarify the novel contributions presented in the extension; - Include a significant additional contribution — such as new experiments providing stronger evidence for existing claims, new theoretical results (theorems, full proofs), or substantial new developments validating new claims. There is no fixed minimum percentage of new content, but the extension should represent a meaningful scientific advance beyond the conference version. Authors should also ensure compliance with any copyright agreements signed with the original venue — in particular, text from papers for which copyright has been transferred to another publisher should not be reused verbatim (though scientific content can, of course, be built upon). --- *Submission Types* - Research Articles - Survey Articles - Resource Articles (benchmarks, datasets, ontologies, tools, knowledge graphs, etc.) Expected length: 10–20 pages using the . --- :date: *Important Dates* - Submission deadline: *June 30, 2026* - Author notification: September 30, 2026 - Revisions: October 31, 2026 - Final notification: November 30, 2026 --- *Submission* Please follow the TGDK submission instructions and select this Special Issue in the submission portal: Full call details are available at: --- *Guest Editors* - Stefano De Giorgis, Vrije Universiteit Amsterdam, Netherlands - Marco Antonio Stranisci, University of Turin, Italy - Luana Bulla, University of Bologna, Italy - Lia Draetta, University of Turin, Italy - Rossana Damiano, University of Turin, Italy - Filip Ilievski, Vrije Universiteit Amsterdam, Netherlands We look forward to your contributions! Best regards, The Guest Editors4e:T49e,As you might have heard, GRAPHIA, an European research project, is building an open knowledge graph to connect Social Sciences and Humanities (SSH) data, making it easier to explore, link, and reuse. We have opened the 1st Call for Pilots for commercial and industry organisations working with Social Sciences and Humanities (SSH) content to join in to explore how the GRAPHIA knowledge graph infrastructure can support real-world products, services, and workflows. Who is this for? Organisations based in the European Research Area such as (but not limited to) scholarly and trade publishers, EdTech providers, data aggregators, SMEs, start-ups, consultancies, or other organisations working with SSH data. Benefits: • Early access to tools, services, and infrastructure • Collaboration with SSH, data, and AI experts • Visibility for your organisation on the GRAPHIA website and communications Deadline for expressions of interest: 5 March 2026 Full details and the short form to express interest can be found here (https://graphia-ssh.eu/call-for-pilots/). In case you are not based in the European Research Area, you can send us your suggestion anyway for consideration.4f:T4aa,As you might have heard, GRAPHIA, an European research project, is building an open knowledge graph to connect Social Sciences and Humanities (SSH) data, making it easier to explore, link, and reuse. We have opened the *1st Call for Pilots* for commercial and industry organisations working with Social Sciences and Humanities (SSH) content to join in to explore how the GRAPHIA knowledge graph infrastructure can support *real-world products, services, and workflows*. *Who is this for?* Organisations based in the European Research Area such as (but not limited to) scholarly and trade publishers, EdTech providers, data aggregators, SMEs, start-ups, consultancies, or other organisations working with SSH data. *Benefits:* • Early access to tools, services, and infrastructure • Collaboration with SSH, data, and AI experts • Visibility for your organisation on the GRAPHIA website and communications *Deadline for expressions of interest:* *5 March 2026* Full details and the short form to express interest can be found . In case you are not based in the European Research Area, you can send us your suggestion anyway for consideration.50:T513,Hi all, As a reminder, the GRAPHIA project (https://graphia-ssh.eu/) is inviting researchers in the social sciences and humanities (SSH) to take part in a short survey on how they interact with knowledge graphs, particularly when supported by Large Language Models (LLMs). You have one more week to participate! We are interested in understanding how researchers explore, query, and make sense of structured research data — whether through natural language interfaces (e.g. chat-based tools) or more formal query mechanisms (e.g. menus, filters, or query languages). Your input will directly inform the design of future tools and interaction models within GRAPHIA. Survey details • ⏱️ Duration: ~15 minutes • 👥 Open to SSH researchers at all career stages • 🧠 No prior experience with knowledge graphs is required • 🗓️ Deadline: 16 January 2026 👉 Take the survey here: https://forms.gle/rna8NcybYri1wft69 GRAPHIA is committed to a co-design approach, ensuring that emerging research infrastructures reflect real user practices and needs. By sharing your perspective, you will help shape how knowledge graphs and AI-supported interfaces evolve for SSH research. Thank you for considering contributing your experience. Kind regards, Ursula, on behalf of the GRAPHIA project51:T55f,*Hi all,* As a reminder, the *GRAPHIA project* () is inviting researchers in the *social sciences and humanities (SSH)* to take part in a short survey on how they interact with *knowledge graphs*, particularly when supported by *Large Language Models (LLMs)*. You have one more week to participate! We are interested in understanding how researchers explore, query, and make sense of structured research data — whether through *natural language interfaces* (e.g. chat-based tools) or *more formal query mechanisms* (e.g. menus, filters, or query languages). Your input will directly inform the design of future tools and interaction models within GRAPHIA. *Survey details* • :stopwatch: Duration: ~15 minutes • :busts_in_silhouette: Open to SSH researchers at all career stages • :brain: No prior experience with knowledge graphs is required • :spiral_calendar_pad: *Deadline: 16 January 2026* :point_right: *Take the survey here:* GRAPHIA is committed to a co-design approach, ensuring that emerging research infrastructures reflect real user practices and needs. By sharing your perspective, you will help shape how knowledge graphs and AI-supported interfaces evolve for SSH research. 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","type":"text"},{"text":"http://www-sop.inria.fr/acacia/cours/essi2006/Scientific%20American_%20Feature%20Art[…]zOuM83n7g5cw0bf0_I9sXCHEbcpDk1HZ7c0XHTKp3VhpBmAWh7-TB0iFu5r2","type":"text","marks":[{"type":"link","attrs":{"href":"http://www-sop.inria.fr/acacia/cours/essi2006/Scientific%20American_%20Feature%20Article_%20The%20Semantic%20Web_%20May%202001.pdf?utm_source=hs_email&utm_medium=email&_hsenc=p2ANqtz--6nclpLU8pzOuM83n7g5cw0bf0_I9sXCHEbcpDk1HZ7c0XHTKp3VhpBmAWh7-TB0iFu5r2"}}]}]}]},"body_plaintext":"Quick question: Have you read the original Semantic Web article? Have you read it lately? 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","type":"text"},{"url":"http://www-sop.inria.fr/acacia/cours/essi2006/Scientific%20American_%20Feature%20Article_%20The%20Semantic%20Web_%20May%202001.pdf?utm_source=hs_email&utm_medium=email&_hsenc=p2ANqtz--6nclpLU8pzOuM83n7g5cw0bf0_I9sXCHEbcpDk1HZ7c0XHTKp3VhpBmAWh7-TB0iFu5r2","text":"http://www-sop.inria.fr/acacia/cours/essi2006/Scientific%20American_%20Feature%20Art[…]zOuM83n7g5cw0bf0_I9sXCHEbcpDk1HZ7c0XHTKp3VhpBmAWh7-TB0iFu5r2","type":"link"}]}]}],"markdown":"Quick question: Have you read the original Semantic Web article? Have you read it lately? Because at least for me it explains AI agents better than anything I have read. ","permalink":"https://knowledgegraphconf.slack.com/archives/C012R3KJBF0/p1776714425182689","parent_slack_message_id":null,"username":null,"icon":null,"is_shared":false},"cover_image_file_id":null,"cover_image_url":null,"author":{"id":"3cd41b35-dea3-4b35-be2d-8d0be245efc8","preferred_name":"Deb 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for Papers: GenAIK + NORA Workshop at IJCAI-ECAI 2026 in Bremen, August 15–17","slug":"call-for-papers-genaik-nora-workshop-at-ijcai-ecai","description":null,"feed_id":"455b4e71-ff15-4968-bde2-88e777291f52","post_detail_display_format":"discussion","author_profile_id":"098d2e7e-b90b-45b8-8d29-4d86eee9ee41","body_prosemirror":{"type":"doc","content":[{"type":"paragraph","content":[{"text":"🚨","type":"text"},{"text":" Call for Papers – GenAIK + NORA @ IJCAI-ECAI 2026","type":"text"},{"type":"hardBreak"},{"text":"📍","type":"text"},{"text":" Bremen, Germany | ","type":"text"},{"text":"📅","type":"text"},{"text":" 15–17 August 2026","type":"text"},{"type":"hardBreak"},{"text":"We are excited to invite submissions to the joint workshop on 𝗚𝗲𝗻𝗲𝗿𝗮𝘁𝗶𝘃𝗲 𝗔𝗜 𝗮𝗻𝗱 𝗞𝗻𝗼𝘄𝗹𝗲𝗱𝗴𝗲 𝗚𝗿𝗮𝗽𝗵𝘀 (𝗚𝗲𝗻𝗔𝗜𝗞) and 𝗞𝗻𝗼𝘄𝗹𝗲𝗱𝗴𝗲 𝗚𝗿𝗮𝗽𝗵𝘀 & 𝗔𝗴𝗲𝗻𝘁𝗶𝗰 𝗦𝘆𝘀𝘁𝗲𝗺𝘀 𝗜𝗻𝘁𝗲𝗿𝗽𝗹𝗮𝘆 (𝗡𝗢𝗥𝗔).","type":"text"},{"type":"hardBreak"},{"type":"hardBreak"},{"text":"📢","type":"text"},{"text":" Topics include (but are not limited to):","type":"text"},{"type":"hardBreak"},{"text":"• KG construction & refinement with LLMs and agents","type":"text"},{"type":"hardBreak"},{"text":"• KG-grounded generation","type":"text"},{"type":"hardBreak"},{"text":"• Neuro-symbolic reasoning & explainability","type":"text"},{"type":"hardBreak"},{"text":"• Agent memory, planning, and coordination","type":"text"},{"type":"hardBreak"},{"text":"• Trustworthy AI: hallucination reduction, bias, robustness","type":"text"},{"type":"hardBreak"},{"text":"• Applications in healthcare, finance, education, and more","type":"text"},{"type":"hardBreak"},{"type":"hardBreak"},{"text":"📅","type":"text"},{"text":" 𝗜𝗺𝗽𝗼𝗿𝘁𝗮𝗻𝘁 𝗗𝗮𝘁𝗲𝘀:","type":"text"},{"type":"hardBreak"},{"text":"- Submission Deadline: 7 May 2026","type":"text"},{"type":"hardBreak"},{"text":"- Notification of Acceptance: 10 June 2026","type":"text"},{"type":"hardBreak"},{"text":"- Camera-ready Paper Due: 25 June 2026","type":"text"},{"type":"hardBreak"},{"type":"hardBreak"},{"text":"https://genetasefa.github.io/GenAIK2026/","type":"text","marks":[{"type":"link","attrs":{"href":"https://genetasefa.github.io/GenAIK2026/"}}]},{"type":"hardBreak"},{"type":"hardBreak"},{"text":"https://www.linkedin.com/feed/update/urn:li:activity:7448712432358715392","type":"text","marks":[{"type":"link","attrs":{"href":"https://www.linkedin.com/feed/update/urn:li:activity:7448712432358715392"}}]}]}]},"body_plaintext":"🚨 Call for Papers – GenAIK + NORA @ IJCAI-ECAI 2026\n📍 Bremen, Germany | 📅 15–17 August 2026\nWe are excited to invite submissions to the joint workshop on 𝗚𝗲𝗻𝗲𝗿𝗮𝘁𝗶𝘃𝗲 𝗔𝗜 𝗮𝗻𝗱 𝗞𝗻𝗼𝘄𝗹𝗲𝗱𝗴𝗲 𝗚𝗿𝗮𝗽𝗵𝘀 (𝗚𝗲𝗻𝗔𝗜𝗞) and 𝗞𝗻𝗼𝘄𝗹𝗲𝗱𝗴𝗲 𝗚𝗿𝗮𝗽𝗵𝘀 & 𝗔𝗴𝗲𝗻𝘁𝗶𝗰 𝗦𝘆𝘀𝘁𝗲𝗺𝘀 𝗜𝗻𝘁𝗲𝗿𝗽𝗹𝗮𝘆 (𝗡𝗢𝗥𝗔).\n\n📢 Topics include (but are not limited to):\n• KG construction & refinement with LLMs and agents\n• KG-grounded generation\n• Neuro-symbolic reasoning & explainability\n• Agent memory, planning, and coordination\n• Trustworthy AI: hallucination reduction, bias, robustness\n• Applications in healthcare, finance, education, and more\n\n📅 𝗜𝗺𝗽𝗼𝗿𝘁𝗮𝗻𝘁 𝗗𝗮𝘁𝗲𝘀:\n- Submission Deadline: 7 May 2026\n- Notification of Acceptance: 10 June 2026\n- Camera-ready Paper Due: 25 June 2026\n\nhttps://genetasefa.github.io/GenAIK2026/\n\nhttps://www.linkedin.com/feed/update/urn:li:activity:7448712432358715392","source":"slack","edited_at":"2026-04-14T17:23:22.682+00:00","version":1,"is_published":true,"file_attachments_count":0,"reactions_count":3,"comments_count":0,"slack_message":{"id":"4b5a0e68-ef11-4e36-b96d-519be0ba0871","message_ts":"1776187377.725449","blocks":[{"type":"rich_text","block_id":"dtrPS","elements":[{"type":"rich_text_section","elements":[{"name":"rotating_light","type":"emoji","unicode":"1f6a8"},{"text":" Call for Papers – GenAIK + NORA @ IJCAI-ECAI 2026\n","type":"text"},{"name":"round_pushpin","type":"emoji","unicode":"1f4cd"},{"text":" Bremen, Germany | ","type":"text"},{"name":"date","type":"emoji","unicode":"1f4c5"},{"text":" 15–17 August 2026\nWe are excited to invite submissions to the joint workshop on 𝗚𝗲𝗻𝗲𝗿𝗮𝘁𝗶𝘃𝗲 𝗔𝗜 𝗮𝗻𝗱 𝗞𝗻𝗼𝘄𝗹𝗲𝗱𝗴𝗲 𝗚𝗿𝗮𝗽𝗵𝘀 (𝗚𝗲𝗻𝗔𝗜𝗞) and 𝗞𝗻𝗼𝘄𝗹𝗲𝗱𝗴𝗲 𝗚𝗿𝗮𝗽𝗵𝘀 & 𝗔𝗴𝗲𝗻𝘁𝗶𝗰 𝗦𝘆𝘀𝘁𝗲𝗺𝘀 𝗜𝗻𝘁𝗲𝗿𝗽𝗹𝗮𝘆 (𝗡𝗢𝗥𝗔).\n\n","type":"text"},{"name":"loudspeaker","type":"emoji","unicode":"1f4e2"},{"text":" Topics include (but are not limited to):\n• KG construction & refinement with LLMs and agents\n• KG-grounded generation\n• Neuro-symbolic reasoning & explainability\n• Agent memory, planning, and coordination\n• Trustworthy AI: hallucination reduction, bias, robustness\n• Applications in healthcare, finance, education, and more\n\n","type":"text"},{"name":"date","type":"emoji","unicode":"1f4c5"},{"text":" 𝗜𝗺𝗽𝗼𝗿𝘁𝗮𝗻𝘁 𝗗𝗮𝘁𝗲𝘀:\n- Submission Deadline: 7 May 2026\n- Notification of Acceptance: 10 June 2026\n- Camera-ready Paper Due: 25 June 2026\n\n","type":"text"},{"url":"https://genetasefa.github.io/GenAIK2026/","type":"link"},{"text":"\n\n","type":"text"},{"url":"https://www.linkedin.com/feed/update/urn:li:activity:7448712432358715392","type":"link"}]}]}],"markdown":":rotating_light: Call for Papers – GenAIK + NORA @ IJCAI-ECAI 2026\n:round_pushpin: Bremen, Germany | :date: 15–17 August 2026\nWe are excited to invite submissions to the joint workshop on 𝗚𝗲𝗻𝗲𝗿𝗮𝘁𝗶𝘃𝗲 𝗔𝗜 𝗮𝗻𝗱 𝗞𝗻𝗼𝘄𝗹𝗲𝗱𝗴𝗲 𝗚𝗿𝗮𝗽𝗵𝘀 (𝗚𝗲𝗻𝗔𝗜𝗞) and 𝗞𝗻𝗼𝘄𝗹𝗲𝗱𝗴𝗲 𝗚𝗿𝗮𝗽𝗵𝘀 & 𝗔𝗴𝗲𝗻𝘁𝗶𝗰 𝗦𝘆𝘀𝘁𝗲𝗺𝘀 𝗜𝗻𝘁𝗲𝗿𝗽𝗹𝗮𝘆 (𝗡𝗢𝗥𝗔).\n\n:loudspeaker: Topics include (but are not limited to):\n• KG construction & refinement with LLMs and agents\n• KG-grounded generation\n• Neuro-symbolic reasoning & explainability\n• Agent memory, planning, and coordination\n• Trustworthy AI: hallucination reduction, bias, robustness\n• Applications in healthcare, finance, education, and more\n\n:date: 𝗜𝗺𝗽𝗼𝗿𝘁𝗮𝗻𝘁 𝗗𝗮𝘁𝗲𝘀:\n- Submission Deadline: 7 May 2026\n- Notification of Acceptance: 10 June 2026\n- Camera-ready Paper Due: 25 June 2026\n\n\n\n","permalink":"https://knowledgegraphconf.slack.com/archives/C012R3KJBF0/p1776187377725449","parent_slack_message_id":null,"username":null,"icon":null,"is_shared":false},"cover_image_file_id":null,"cover_image_url":null,"author":{"id":"098d2e7e-b90b-45b8-8d29-4d86eee9ee41","preferred_name":"Genet A.","preferred_image_original":null,"preferred_image_1024":null,"preferred_image_512":"https://secure.gravatar.com/avatar/324526b4dd9dd544373cae110fd1149d.jpg?s=512&d=https%3A%2F%2Fa.slack-edge.com%2Fdf10d%2Fimg%2Favatars%2Fava_0007-512.png","preferred_image_192":"https://secure.gravatar.com/avatar/324526b4dd9dd544373cae110fd1149d.jpg?s=192&d=https%3A%2F%2Fa.slack-edge.com%2Fdf10d%2Fimg%2Favatars%2Fava_0007-192.png","preferred_image_72":"https://secure.gravatar.com/avatar/324526b4dd9dd544373cae110fd1149d.jpg?s=72&d=https%3A%2F%2Fa.slack-edge.com%2Fdf10d%2Fimg%2Favatars%2Fava_0007-72.png","preferred_image_48":"https://secure.gravatar.com/avatar/324526b4dd9dd544373cae110fd1149d.jpg?s=48&d=https%3A%2F%2Fa.slack-edge.com%2Fdf10d%2Fimg%2Favatars%2Fava_0007-48.png","preferred_image_32":"https://secure.gravatar.com/avatar/324526b4dd9dd544373cae110fd1149d.jpg?s=32&d=https%3A%2F%2Fa.slack-edge.com%2Fdf10d%2Fimg%2Favatars%2Fava_0007-32.png","preferred_image_24":"https://secure.gravatar.com/avatar/324526b4dd9dd544373cae110fd1149d.jpg?s=24&d=https%3A%2F%2Fa.slack-edge.com%2Fdf10d%2Fimg%2Favatars%2Fava_0007-24.png","slack_profile_id":"U08429PBC74","is_team_member":false,"slack_profile":{"id":"U08429PBC74","is_admin":false,"is_bot":false,"is_forgotten":false,"deleted":false}},"best_answer_message_id":null,"selected_answer_message_ids":[],"selected_answer_count":0,"feed":{"id":"455b4e71-ff15-4968-bde2-88e777291f52","public_id":"feed_4U236VVKNSzq","label":"Share","slug":"share","is_posting_from_site_allowed":false,"allow_selected_answer":false,"visibility":"public"},"references":{"mentioned_slack_users":[],"mentioned_slack_channels":[],"custom_emojis":[],"urls":[{"url":"https://genetasefa.github.io/GenAIK2026/","is_image":false,"is_video":false,"order_seen":0,"is_embedded_media":false},{"url":"https://www.linkedin.com/feed/update/urn:li:activity:7448712432358715392","is_image":false,"is_video":false,"order_seen":1,"is_embedded_media":false}]}},{"id":"pvqtn2tkb6xk","message_id":"msg_6KrDB0XOdD59","created_at":"2026-04-07T06:09:18.0856+00:00","content_created_at":"2026-04-07T06:09:12.979+00:00","latest_activity_at":"2026-04-07T06:09:12.979+00:00","title":"Call for Papers: Special Issue on Neuro-Symbolic Modeling for Human-Centric AI – Deadline June 30, 2026","slug":"call-for-papers-special-issue-on-neuro-symbolic-mo","description":null,"feed_id":"455b4e71-ff15-4968-bde2-88e777291f52","post_detail_display_format":"discussion","author_profile_id":"d1959d78-621d-4d99-b3f0-09341a85c7bd","body_prosemirror":{"type":"doc","content":[{"type":"paragraph","content":[{"text":"📣","type":"text"},{"text":" ","type":"text","marks":[{"type":"bold"}]},{"text":"[CfP] TGDK Special Issue: Neuro-Symbolic Modeling for Human-Centric AI — Submission Deadline: June 30, 2026","type":"text"},{"type":"hardBreak"},{"type":"hardBreak"},{"text":"Dear Colleagues,","type":"text"},{"type":"hardBreak"},{"type":"hardBreak"},{"text":"We are pleased to invite you to submit your work to the Special Issue on ","type":"text"},{"text":"Neuro-Symbolic Modeling for Human-Centric AI","type":"text","marks":[{"type":"link","attrs":{"href":"https://drops.dagstuhl.de/entities/journal/TGDK#cfp-si-neuro-symbolic-modeling-for-human-centric-ai"}}]},{"text":", published in the ","type":"text"},{"text":"Transactions on Graph Data and Knowledge (TGDK)","type":"text","marks":[{"type":"link","attrs":{"href":"https://drops.dagstuhl.de/entities/journal/TGDK"}}]},{"text":" — a Diamond Open Access journal by Dagstuhl Publishing (free for both authors and readers).","type":"text"},{"type":"hardBreak"},{"type":"hardBreak"},{"text":"---","type":"text"},{"type":"hardBreak"},{"type":"hardBreak"},{"text":"Motivation","type":"text","marks":[{"type":"bold"}]},{"type":"hardBreak"},{"type":"hardBreak"},{"text":"The alignment of AI technologies with people's behaviors and worldviews has become a central challenge across many sectors of Computer Science. The pervasive diffusion of Large Language Models (LLMs) requires important efforts to ensure fairness and representativity towards all social and cultural groups, potentially considering different identities that characterize potential end-users of these technologies. This special issue welcomes contributions on the development of graph-based abstractions and hybrid neuro-symbolic approaches for human-centered AI.","type":"text"},{"type":"hardBreak"},{"type":"hardBreak"},{"text":"---","type":"text"},{"type":"hardBreak"},{"type":"hardBreak"},{"text":"Topics of Interest","type":"text","marks":[{"type":"bold"}]},{"type":"hardBreak"},{"type":"hardBreak"},{"text":"We solicit research, resource, and survey articles aligned with the scope of TGDK, covering (but not limited to):","type":"text"},{"type":"hardBreak"},{"type":"hardBreak"},{"text":"Ontology modeling and knowledge representation for Human-Centric AI","type":"text","marks":[{"type":"bold"}]},{"type":"hardBreak"},{"text":" - Knowledge representation for reducing bias in AI","type":"text"},{"type":"hardBreak"},{"text":" - Ontologies of identity dimensions and psychology for AI","type":"text"},{"type":"hardBreak"},{"text":" - Ontologies of sociological and communication theories for AI","type":"text"},{"type":"hardBreak"},{"text":" - Linked Data approaches for Human-Centric AI","type":"text"},{"type":"hardBreak"},{"type":"hardBreak"},{"text":"Data quality, integration and provenance for Human-Centric AI","type":"text","marks":[{"type":"bold"}]},{"type":"hardBreak"},{"text":" - FAIR and CARE principles for AI models","type":"text"},{"type":"hardBreak"},{"text":" - Graph-based provenance approaches for AI models","type":"text"},{"type":"hardBreak"},{"text":" - Incorporating cultural metadata into AI workflows","type":"text"},{"type":"hardBreak"},{"text":" - KG-driven approaches for bias detection and mitigation in archives","type":"text"},{"type":"hardBreak"},{"type":"hardBreak"},{"text":"LLM integration with graph-structured knowledge for fair AI","type":"text","marks":[{"type":"bold"}]},{"type":"hardBreak"},{"text":" - Question answering with LLMs and graph-structured knowledge","type":"text"},{"type":"hardBreak"},{"text":" - Reducing LLM hallucinations with graph-structured knowledge","type":"text"},{"type":"hardBreak"},{"text":" - Retrieval-Augmented Generation using graph-structured knowledge","type":"text"},{"type":"hardBreak"},{"text":" - Enhancing graph-structured knowledge using LLMs","type":"text"},{"type":"hardBreak"},{"type":"hardBreak"},{"text":"Logic and reasoning for Explainable AI","type":"text","marks":[{"type":"bold"}]},{"type":"hardBreak"},{"text":" - Logic-based methods for governance, ethical frameworks, and legal compliance of AI","type":"text"},{"type":"hardBreak"},{"text":" - Extraction of logic-based representations for explainable AI","type":"text"},{"type":"hardBreak"},{"text":" - Graph-based constraint languages for explainable AI","type":"text"},{"type":"hardBreak"},{"type":"hardBreak"},{"text":"---","type":"text"},{"type":"hardBreak"},{"type":"hardBreak"},{"text":"Extended Versions of Conference Papers","type":"text","marks":[{"type":"bold"}]},{"type":"hardBreak"},{"type":"hardBreak"},{"text":"We explicitly welcome extended versions of previously published conference papers. If you have recently presented relevant work at a conference (e.g., NeSy, ISWC, ESWC, AAAI, IJCAI, ACL or similar venues), we strongly encourage you to consider submitting an extended version to this Special Issue.","type":"text"},{"type":"hardBreak"},{"type":"hardBreak"},{"text":"Extended versions must:","type":"text"},{"type":"hardBreak"},{"text":"- Clearly state in the introduction that the submission is an extension of a prior conference paper, with an explicit reference to it;","type":"text"},{"type":"hardBreak"},{"text":"- Clarify the novel contributions presented in the extension;","type":"text"},{"type":"hardBreak"},{"text":"- Include a significant additional contribution — such as new experiments providing stronger evidence for existing claims, new theoretical results (theorems, full proofs), or substantial new developments validating new claims.","type":"text"},{"type":"hardBreak"},{"type":"hardBreak"},{"text":"There is no fixed minimum percentage of new content, but the extension should represent a meaningful scientific advance beyond the conference version. Authors should also ensure compliance with any copyright agreements signed with the original venue — in particular, text from papers for which copyright has been transferred to another publisher should not be reused verbatim (though scientific content can, of course, be built upon).","type":"text"},{"type":"hardBreak"},{"type":"hardBreak"},{"text":"---","type":"text"},{"type":"hardBreak"},{"type":"hardBreak"},{"text":"Submission Types","type":"text","marks":[{"type":"bold"}]},{"type":"hardBreak"},{"type":"hardBreak"},{"text":"- Research Articles","type":"text"},{"type":"hardBreak"},{"text":"- Survey Articles","type":"text"},{"type":"hardBreak"},{"text":"- Resource Articles (benchmarks, datasets, ontologies, tools, knowledge graphs, etc.)","type":"text"},{"type":"hardBreak"},{"type":"hardBreak"},{"text":"Expected length: 10–20 pages using the ","type":"text"},{"text":"TGDK single-column LaTeX template","type":"text","marks":[{"type":"link","attrs":{"href":"https://drops.dagstuhl.de/entities/journal/TGDK#author"}}]},{"text":".","type":"text"},{"type":"hardBreak"},{"type":"hardBreak"},{"text":"---","type":"text"},{"type":"hardBreak"},{"type":"hardBreak"},{"text":"📅","type":"text"},{"text":" Important Dates","type":"text","marks":[{"type":"bold"}]},{"type":"hardBreak"},{"type":"hardBreak"},{"text":"- Submission deadline: ","type":"text"},{"text":"June 30, 2026","type":"text","marks":[{"type":"bold"}]},{"type":"hardBreak"},{"text":"- Author notification: September 30, 2026","type":"text"},{"type":"hardBreak"},{"text":"- Revisions: October 31, 2026","type":"text"},{"type":"hardBreak"},{"text":"- Final notification: November 30, 2026","type":"text"},{"type":"hardBreak"},{"type":"hardBreak"},{"text":"---","type":"text"},{"type":"hardBreak"},{"type":"hardBreak"},{"text":"Submission","type":"text","marks":[{"type":"bold"}]},{"type":"hardBreak"},{"type":"hardBreak"},{"text":"Please follow the TGDK submission instructions and select this Special Issue in the submission portal:","type":"text"},{"type":"hardBreak"},{"text":"https://journal-submission.dagstuhl.de/TGDK/","type":"text","marks":[{"type":"link","attrs":{"href":"https://journal-submission.dagstuhl.de/TGDK/"}}]},{"type":"hardBreak"},{"type":"hardBreak"},{"text":"Full call details are available at:","type":"text"},{"type":"hardBreak"},{"text":"https://drops.dagstuhl.de/entities/journal/TGDK#cfp-si-neuro-symbolic-modeling-for-human-centric-ai","type":"text","marks":[{"type":"link","attrs":{"href":"https://drops.dagstuhl.de/entities/journal/TGDK#cfp-si-neuro-symbolic-modeling-for-human-centric-ai"}}]},{"type":"hardBreak"},{"type":"hardBreak"},{"text":"---","type":"text"},{"type":"hardBreak"},{"type":"hardBreak"},{"text":"Guest Editors","type":"text","marks":[{"type":"bold"}]},{"type":"hardBreak"},{"type":"hardBreak"},{"text":"- Stefano De Giorgis, Vrije Universiteit Amsterdam, Netherlands","type":"text"},{"type":"hardBreak"},{"text":"- Marco Antonio Stranisci, University of Turin, Italy","type":"text"},{"type":"hardBreak"},{"text":"- Luana Bulla, University of Bologna, Italy","type":"text"},{"type":"hardBreak"},{"text":"- Lia Draetta, University of Turin, Italy","type":"text"},{"type":"hardBreak"},{"text":"- Rossana Damiano, University of Turin, Italy","type":"text"},{"type":"hardBreak"},{"text":"- Filip Ilievski, Vrije Universiteit Amsterdam, Netherlands","type":"text"},{"type":"hardBreak"},{"type":"hardBreak"},{"text":"We look forward to your contributions!","type":"text"},{"type":"hardBreak"},{"type":"hardBreak"},{"text":"Best regards,","type":"text"},{"type":"hardBreak"},{"text":"The Guest Editors","type":"text"}]}]},"body_plaintext":"$4b","source":"slack","edited_at":null,"version":0,"is_published":true,"file_attachments_count":0,"reactions_count":3,"comments_count":0,"slack_message":{"id":"79abcd5f-df62-46ba-8efe-b06e07983c0e","message_ts":"1775542152.979109","blocks":[{"type":"rich_text","block_id":"ZVixN","elements":[{"type":"rich_text_section","elements":[{"name":"mega","type":"emoji","style":{"bold":true},"unicode":"1f4e3"},{"text":" ","type":"text","style":{"bold":true}},{"text":"[CfP] TGDK Special Issue: Neuro-Symbolic Modeling for Human-Centric AI — Submission Deadline: June 30, 2026\n\nDear Colleagues,\n\nWe are pleased to invite you to submit your work to the Special Issue on ","type":"text"},{"url":"https://drops.dagstuhl.de/entities/journal/TGDK#cfp-si-neuro-symbolic-modeling-for-human-centric-ai","text":"Neuro-Symbolic Modeling for Human-Centric AI","type":"link","style":{"bold":true}},{"text":", published in the ","type":"text"},{"url":"https://drops.dagstuhl.de/entities/journal/TGDK","text":"Transactions on Graph Data and Knowledge (TGDK)","type":"link","style":{"italic":true}},{"text":" — a Diamond Open Access journal by Dagstuhl Publishing (free for both authors and readers).\n\n---\n\n","type":"text"},{"text":"Motivation","type":"text","style":{"bold":true}},{"text":"\n\nThe alignment of AI technologies with people's behaviors and worldviews has become a central challenge across many sectors of Computer Science. The pervasive diffusion of Large Language Models (LLMs) requires important efforts to ensure fairness and representativity towards all social and cultural groups, potentially considering different identities that characterize potential end-users of these technologies. This special issue welcomes contributions on the development of graph-based abstractions and hybrid neuro-symbolic approaches for human-centered AI.\n\n---\n\n","type":"text"},{"text":"Topics of Interest","type":"text","style":{"bold":true}},{"text":"\n\nWe solicit research, resource, and survey articles aligned with the scope of TGDK, covering (but not limited to):\n\n","type":"text"},{"text":"Ontology modeling and knowledge representation for Human-Centric AI","type":"text","style":{"bold":true}},{"text":"\n - Knowledge representation for reducing bias in AI\n - Ontologies of identity dimensions and psychology for AI\n - Ontologies of sociological and communication theories for AI\n - Linked Data approaches for Human-Centric AI\n\n","type":"text"},{"text":"Data quality, integration and provenance for Human-Centric AI","type":"text","style":{"bold":true}},{"text":"\n - FAIR and CARE principles for AI models\n - Graph-based provenance approaches for AI models\n - Incorporating cultural metadata into AI workflows\n - KG-driven approaches for bias detection and mitigation in archives\n\n","type":"text"},{"text":"LLM integration with graph-structured knowledge for fair AI","type":"text","style":{"bold":true}},{"text":"\n - Question answering with LLMs and graph-structured knowledge\n - Reducing LLM hallucinations with graph-structured knowledge\n - Retrieval-Augmented Generation using graph-structured knowledge\n - Enhancing graph-structured knowledge using LLMs\n\n","type":"text"},{"text":"Logic and reasoning for Explainable AI","type":"text","style":{"bold":true}},{"text":"\n - Logic-based methods for governance, ethical frameworks, and legal compliance of AI\n - Extraction of logic-based representations for explainable AI\n - Graph-based constraint languages for explainable AI\n\n---\n\n","type":"text"},{"text":"Extended Versions of Conference Papers","type":"text","style":{"bold":true}},{"text":"$4c","type":"text"},{"text":"Submission Types","type":"text","style":{"bold":true}},{"text":"\n\n- Research Articles\n- Survey Articles\n- Resource Articles (benchmarks, datasets, ontologies, tools, knowledge graphs, etc.)\n\nExpected length: 10–20 pages using the ","type":"text"},{"url":"https://drops.dagstuhl.de/entities/journal/TGDK#author","text":"TGDK single-column LaTeX template","type":"link"},{"text":".\n\n---\n\n","type":"text"},{"name":"date","type":"emoji","style":{"bold":true},"unicode":"1f4c5"},{"text":" Important Dates","type":"text","style":{"bold":true}},{"text":"\n\n- Submission deadline: ","type":"text"},{"text":"June 30, 2026","type":"text","style":{"bold":true}},{"text":"\n- Author notification: September 30, 2026\n- Revisions: October 31, 2026\n- Final notification: November 30, 2026\n\n---\n\n","type":"text"},{"text":"Submission","type":"text","style":{"bold":true}},{"text":"\n\nPlease follow the TGDK submission instructions and select this Special Issue in the submission portal:\n","type":"text"},{"url":"https://journal-submission.dagstuhl.de/TGDK/","type":"link"},{"text":"\n\nFull call details are available at:\n","type":"text"},{"url":"https://drops.dagstuhl.de/entities/journal/TGDK#cfp-si-neuro-symbolic-modeling-for-human-centric-ai","type":"link"},{"text":"\n\n---\n\n","type":"text"},{"text":"Guest Editors","type":"text","style":{"bold":true}},{"text":"\n\n- Stefano De Giorgis, Vrije Universiteit Amsterdam, Netherlands\n- Marco Antonio Stranisci, University of Turin, Italy\n- Luana Bulla, University of Bologna, Italy\n- Lia Draetta, University of Turin, Italy\n- Rossana Damiano, University of Turin, Italy\n- Filip Ilievski, Vrije Universiteit Amsterdam, Netherlands\n\nWe look forward to your contributions!\n\nBest regards,\nThe Guest 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