Hi All, You are invited to submit your work at LLMS4KGOE, please find more information below.
Call for Papers: LLMS4KGOE 2026 (ESWC 2026 Workshop) The Call for Papers for the First Workshop on LLM-driven Knowledge Graph and Ontology Engineering (LLMS4KGOE 2026)—co-located with ESWC 2026—is now live. About: While Semantic Web progress depends on high-quality ontologies, traditional ontology engineering is slow, expert-driven, and hard to scale. Large Language Models offer a major shift by potentially speeding up and democratizing ontology creation, enabling non–computer scientists to build models. However, this promise comes with serious risks: LLM-generated ontologies may be low-quality, incoherent, or formally incorrect, and such flaws would propagate into downstream AI systems. The workshop therefore targets the intersection of LLMs, semantic technologies, and ontology engineering, focusing on both opportunities and unresolved challenges—such as automated ontology pipelines, evaluation methods, and techniques to reduce hallucinations—across theoretical and practical dimensions. Focus: How large language models can be used to create, refine, and evaluate high-quality ontologies and knowledge graphs, with emphasis on: Robustness & hallucination mitigation Semantic consistency Human-in-the-loop workflows Topics of interest include (but are not limited to): * LLM-to-KG with schema constraints: Enforcing structured templates and ontology schemas during triple generation. * Education & UX: Developing LLM-driven tutors for CQ/axiom authoring and automated documentation. * Evidence-linked triple extraction: Capturing direct evidence sentences and document sources for traceability. * Hallucination benchmarking: Metrics and datasets for measuring hallucination severity in KG extraction. * Post-hoc KG repair: Applying symbolic reasoners and neural consistency models to detect/correct errors. * Calibration and abstention: Incorporating probabilistic calibration to allow abstention on uncertain links. * Robustness and red-teaming: Stress-testing model robustness using adversarial inputs and perturbations. * Domain applications: Deploying KG within domains (e.g., biomedical, climate) to quantify decision impact. * Lifecycle and Maintenance: LLM-assisted ontology evolution, versioning, CI/CD integration, and refactoring. * Modular Evaluation & Benchmarks: Component-level metrics, task cards, and error taxonomies. * Provenance & Governance: Designing evidence-traceable axioms, audit trails, and governance mechanisms. Submission Single-blind peer review Proceedings planned in CEUR (non-archival option available) Key Dates (2026) • Paper submission deadline: Feb 20, 2026 • Accepted papers online: Apr 15, 2026 • Workshop: aligned with ESWC 2026 (ESWC website: https://2026.eswc-conferences.org/) Link: Website: https://koncordantlab.github.io/LLM4KGOE-ESWC/ EasyChair submission: <https://2026.eswc-conferences.org/> https://easychair.org/my2/conference?conf=llms4kgoe2026 Organization Organized by Aryan Singh Dalal, Cogan Shimizu, Kathleen Jagodnik, Maria Maleshkova, Hande McGinty, with a program committee spanning academia and industry (TNO, Bosch Research, Inria, Univ. of Bologna, UPM, Univ. of Amsterdam, and others). If your work sits at the intersection of LLMs, semantic technologies, and KG/ontology engineering—methodological, applied, or evaluative, we’d love to see your submission and have you join us at ESWC 2026. **I understand my working hours may not parallel your working hours. Please feel free to only reply at your time** Best regards, Aryan Singh Dalal Linkedin<https://www.linkedin.com/in/aryan-singh-dalal-4914911b1/>, GitHub<https://github.com/aryand1> Koncordant Lab<https://www.koncordantlab.com/>, DaSe Lab<https://daselab.cs.ksu.edu/people/aryan-dalal>, Farms Lab<https://farmslab.k-state.edu/team-members/graduate-students/dalal/> Graduate Research Assistant Ph.D. Candidate | Department of Computer Science Kansas State University | Manhattan, KS 66502 USA
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