Hi everyone, posting here an opportunity, almost unbelievable that it's already 10 years that we've been going on... 📢 Last few weeks left to submit to CAOS 2026 — Cognition And OntologieS! Now celebrating its 10th edition, focused on works at the intersection of cognitive science, sub-symbolic reasoning, knowledge representation, and ontologies, exploring how language, reasoning, and cognitive phenomena can be formally and ontologically modeled for both symbolic and neural AI. With the AGI debate heating up and the long-banned "O-word" (Ontology) finally welcome in AI boardrooms, it is an opportunity to dig into the hybrid future of ontologies, knowledge graphs, and LLMs — and what it really takes to move from broad, shallow intelligence toward deeper, human-like cognitive capabilities. 🗓️ Submission deadlines Short & full papers: October 12, 2026 Abstracts (presentation only): October 26, 2026 Co-located with TriCoLore 2026 in Bressanone/Brixen, Italy (1–6 December 2026) Proceedings published in CEUR Workshop Proceedings Bonus tips: Brixen-Bressanone is amazing in December! TriCoLore hosts four more workshop at the intersection of robotics, embodied cognition, neuro-symbolic AI, and epistemic reasoning. Would love to see your work there, check our website! 👉 Submit via EasyChair: easychair.org/conferences?conf=caos10 🔗 Full CFP: caos.inf.unibz.it/index.php/call-for-papers-2026 🏔️ TriCoLore website: tricolore.inf.unibz.it
📣 [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 Neuro-Symbolic Modeling for Human-Centric AI, published in the Transactions on Graph Data and Knowledge (TGDK) — 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 TGDK single-column LaTeX template. --- 📅 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 Editors
