OVERVIEW

SKGi 2026 is motivated by intersection of Knowledge Graphs (KGs) and semantically oriented technologies, in the context of intelligent Agents in productive scenarios, and how these approaches enable scalable, efficient, and trustworthy features in AI applications. As agentic and generative AI rapidly evolves, integrating symbolic and neural methods becomes essential to address challenges such as explainability, data alignment, and system robustness. Topics also include Graph RAG approaches, other scalable approaches to KG construction and exploitation, maintenance and usage, energy-efficient AI, and user-centered KG interfaces. The workshop brings together academic researchers and industry practitioners to discuss practical solutions and the future of Semantic Web technologies in the era of foundation models.

This third edition expands the scope to explicitly include Agentic AI solutions and their intersection with Knowledge Graphs. This reflects the growing industry demand for hybrid symbolic-neural systems that combine the robustness and structure of KGs with the flexibility and generative power of foundation models.

AIM & SCOPE

• Researchers in Semantic Web, Knowledge Representation, LLMs, and Hybrid AI

• Engineers and practitioners deploying KG/LLM systems in industry

• Tool builders and system architects in hybrid AI systems

• Industry professionals interested in scalable AI knowledge infrastructures

• AI researchers interested in building trustworthy and efficient AI pipelines

• Students and early-career researchers working at the intersection of symbolic and neural AI