About the Workshop

Welcome to the Graph-Augmented LLMs (GaLM): Bridging Language and Structured Knowledge Workshop, taking place on November 12, 2025! This event brings together advanced graph machine learning, LLMs research and practical industrial applications. Our GaLM workshop explores the synergistic convergence of LLMs and graph-based methodologies and its applications with its transformative potential. This integration facilitates advancements in areas such as enhanced reasoning, improved contextual understanding, and robust generalization. We aim to foster discussions on leveraging Graph Neural Networks (GNNs) and graph representation learning to augment LLMs, as well as investigating the application of federated learning and unlearning techniques to address privacy and ethical concerns in this rapidly evolving field. This workshop aims to foster discussions on how graph structures can empower LLMs to achieve improved reasoning, knowledge integration, and data privacy in diverse applications, including but not limited to biomedical, environmental and social-economic systems, with highly structured knowledge.

Call for Papers

The aim of this workshop is to foster discussion around the emerging role of LLMs utilising graph data and computing techniques to enhance LLM capabilities and conversely, vice versa. We will invite original and unpublished research contributions to GaLM in relevant subjects, including, but not limited to:

• Data cleaning, integration, and augmentation with graph-based LLMs
• Graph-enhanced LLM architectures
• LLMs for graph understanding and generation
• LLM-driven graph processing
• Multimodal graph-LLM integration
• Explainability, provenance, security, privacy, benchmarking for graph-based LLMs
• Real-world applications of graph-enhanced LLMs in domains such as healthcare, finance, and social media

Paper Submission: Two types of submissions are invited: full papers (max 10 pages, inc. bibliography) describing mature work, and short papers (max 6 pages, inc. bibliography) describing work-in-progress or case studies. The paper submission must follow the IEEE double-column format as per the IEEE ICDM main conference format guidelines.

Submitted papers will be peer-reviewed and selected on the basis of these reviews. Accepted papers will be presented at the workshop and published in the workshop proceedings.

Submission Link: Click here to submit 

Important Dates

• Workshop papers submission: September 5, 2025
• Workshop papers notification deadline: September 19, 2025
• Early Bird Registration deadline: September 24, 2025
• Camera-ready deadline: September 25, 2025
• Workshop date: Friday 14th November, 2025

Deadlines refer to 23:59 (11:59pm) in the AoE (Anywhere on Earth) time zone.

Keynote

Pan Li, Assistant Professor
School of Electrical and Computer Engineering, Georgia Tech
Talk: Beyond the Sequence: Challenges and Opportunities in Integrating Graphs and LLMs

Abstract: Large Language Models (LLMs) have demonstrated remarkable capabilities in processing and generating sequential text. However, real-world information such as scientific knowledge and enterprise data is rarely a flat sequence; it is a graph of complex relationships. This fundamental mismatch limits an LLM's ability to perform deep relational reasoning, ground its outputs in factual knowledge, and operate safely on sensitive, interconnected data.

Workshop Schedule

Location: Massachusetts, Date: Friday 14th November

10:30–10:35 Steve Huntsman — Introductory Remarks
10:35–11:35 Pan Li — Keynote
11:35–11:50 Presentation
11:50–12:05 Presentation
12:05–12:20 Presentation
12:20–12:30 Presentation

Organizers

• Amit Kumar Jaiswal, IIT (BHU)
• Benyou Wang, CUHK Shenzhen
• Prayag Tiwari, Halmstad University
• Qiuchi Li, University of Copenhagen
• Ruchir Gupta, IIT (BHU)
• Shandar Ahmad, JNU
• Steve Huntsman, Cynnovative