[CfP] Knowledge Graphs and Large Language Models (KG–LLM 2026) @ LREC 2026
Gilles Sérasset
Knowledge Graphs and Large Language Models (KG–LLM 2026) @ LREC 2026
We are pleased to announce the Workshop on Knowledge Graphs and Large Language Models (KG–LLM 2026), to be held in conjunction with LREC 2026 in Palma de Mallorca, Spain, May 16th 2026.
We invite submissions of original research that leverages both Knowledge Graphs (KGs) and Large Language Models (LLMs) in any domain of Natural Language Processing or language resource development.
More information at https://kg-llm.github.io/
Workshop Overview
Large Language Models have become foundational in NLP, yet they continue to face challenges related to bias, hallucination, explainability, environmental impact, and the cost of training. Knowledge Graphs, in contrast, provide high-quality, interpretable, and reusable ontological and linguistic structures that support reasoning, fact checking, and knowledge preservation.
The goal of this workshop is to bring together researchers working at the intersection of these two paradigms, exploring how explicit knowledge and implicit statistical learning can enhance each other. We welcome contributions that investigate, demonstrate, or evaluate systems, methods, or resources integrating both KGs and LLMs.
Topics of Interest
We encourage submissions on (but not limited to):
1. LLMs for Knowledge Graph Engineering
KG modelling, resource creation, and interlinking
- Relation extraction
- Corpus annotation
- Ontology localization
- Creation or expansion of linguistic or knowledge graphs
KG querying and question answering
2. Knowledge Graphs for Large Language Models
Using linguistic or knowledge graphs as training data
- Fine-tuning LLMs using linked linguistic (meta)data
- Knowledge/linguistic graph embeddings
- KGs for model explainability, provenance, and source attribution
- Neural models for under-resourced languages
KG-augmented RAG (KG-RAG)
3. Joint Use of KGs and LLMs in Applications
Combined KG–LLM use cases with structured linguistic data
- Digital humanities applications
- Question answering over graph data
- Fake news and misinformation detection
- Educational applications and assisted learning
- Visualizing academic writing with KGs and LLMs
KG-enhanced chatbots for health and medical contexts
Application Domains
All application domains are welcome (Digital Humanities, FinTech, Linguistics, Education, Cybersecurity, etc.) as long as the work uses both Knowledge Graphs and Large Language Models.
Submission Guidelines
Submission Format: Papers up to 8 pages excluding references.
- Style: All submissions must follow the LREC 2026 format and use the official LREC author kit. (available at https://lrec2026.info/authors-kit/ )
- Review Process: Double-blind peer review. Submissions must be fully anonymized.
- Submission System: Papers must be submitted via the START conference system at https://softconf.com/lrec2026/KGLLM/
- Language Resources: In line with LREC policies, authors are encouraged to describe, document, and share language resources, datasets, models, evaluation tools, or annotation guidelines used or created in their work.
- Accepted Papers: All accepted papers will be included in the LREC 2026 workshop proceedings.
Presentation: Accepted papers will be presented as oral or poster sessions during the workshop.
Important Dates
Paper submission deadline: 26 February 2026
- Notification to authors: 24 March 2026
- Camera-ready due: 30 March 2026
Workshop date: 16 May 2026
Contact
For questions, please contact the workshop organizers at: kg-l...@googlegroups.com
Organizing Committee
- Gilles Sérasset, Université Grenoble Alpes, France
- Katerina Gkirtzou, Athena Research Center, Greece
- Michael Cochez, Ellis Institute Finland & Åbo Akademi, Finland
- Jan-Christoph Kalo, University of Amsterdam, Netherlands