We welcome submissions and participations from intradisciplinary, interdisciplinary and multidisciplinary researchers and industry & public sector practitioners in the areas related to the topics of interest. We especially welcome contributions that provide theoretical insights, propose new approaches, or introduce new grounded solutions in real-world applications such as enterprise, smart assistance & chat, healthcare, finance, tourism, etc.

We invite submissions in this non-exhaustive list of topics of interest, including, but not limited to:

• KG construction, completion, and refinement with GenAI and Agents:
  • Text-to-KG extraction using LLMs (multilingual, multimodal)
  • KG completion, cleaning, and refinement (deduplication, entity resolution)
  • Fact verification, contradiction detection, and consistency checking
  • Human-in-the-loop KG curation and interactive refinement
• KG grounding for information retrieval, including generation, querying, and dialogue:
  • KG-grounded generation / GraphRAG (subgraph retrieval, path-based evidence)
  • Natural language querying of KGs via GenAI (e.g., NL-to-SPARQL)
  • Hybrid QA and dialogue systems combining KGs and GenAI (e.g., Agents)
  • Prompting / controllable generation using KG structure and constraints
  • Context and memory indexing and retrieval for GenAI and agents
• Neuro-symbolic methods, reasoning, and explainability:
  • Hybrid reasoning with rules, constraints, and structured evidence
  • Explainability and verifiable reasoning with provenance/evidence graphs
  • Cross-domain knowledge transfer with KGs and GenAIK
• Representations, embeddings, and temporal/evolving KGs:
  • GenAI for KG embeddings and hybrid vectorgraph representations
  • Temporal KGs, dynamic updates, continual learning, concept drift
  • Ontology learning, schema induction, alignment, and schema evolution
• Trustworthiness, safety, and governance:
  • Bias mitigation using KGs in GenAI and Agentic Systems
  • Hallucination reduction via grounding/constraints; robustness to attacks
  • Uncertainty estimation and calibrated confidence
  • Privacy, access control, and policy-aware KG-grounded generation
• Agentic KGs and real-world systems:
  • Agentic KGs: KGs as long-term memory/state for LLM agents
  • KGs serving agents' memories: Episodic (experiences, events, etc.), Semantic (facts, concepts, etc.), and Procedural (skills, tasks, etc.)
  • KG-aware planning, tool use (query/update), and multi-agent coordination
  • Collaborative & shared agent memories and contexts
  • Context Engineering enhanced by KGs
• GenAI/Agents and KG Applications:
  • Efficient and proactive personal assistance & Personalisation
  • Multi-Lingual & Multi-modal integrations and enablement
  • Personalisation vs Generalisation in GenAI and Agentic systems memory
  • Domain-specific applications: scholarly knowledge, biomedicine & healthcare, finance, education, etc
  • Task-specific applications: personal assistance, dialogue systems, recommender systems, customer service, etc
  • Architectures and pipelines
• Datasets, benchmarks, and evaluation:
  • Benchmark datasets for GenAI or Agents plus KG tasks
  • Evaluation of grounding/faithfulness, factuality, reasoning, robustness
  • Evaluation pitfalls: data leakage, LLM-as-a-judge bias, reproducibility, and reporting standards