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
*All
deadlines are 11:59PM UTC-12:00 (“anywhere on Earth”)*
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-llm-26@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