LLMNet: IEEE LCN 2026 Special Track on Large Language Models and Networking

PAPER REGISTRATION DEADLINE: Jun 08, 2026 (AoE)
PAPER SUBMISSION DEADLINE: Jun 15, 2026 (AoE)

Call For Papers

Scope and Topics

Large Language Models (LLMs) and Generative AI (GenAI) have advanced rapidly in language modelling and related tasks, with their applications now expanding into many other domains. In networking, LLMs and their variants have the potential to address key challenges, including traffic management and classification, configuration management, network migration, and scheduling. However, their full networking potential remains largely underexplored. This special track aims to foster research in this emerging area and bring together the international networking research community working on LLM-driven solutions.

Topics

The topics of interest include, but are not limited to:

  • LLM Applications in Network Operations
  • LLMs for traffic prediction and management
  • LLM-driven anomaly and fault detection in networks
  • LLMs for Network Security and Privacy
  • LLMs for detecting malware in network traffic
  • LLMs in Networked System Optimization
  • LLM-guided routing and congestion control
  • Machine-to-machine LLM
  • Network configuration and optimization through Large GenAI models
  • Benchmarking reasoning and planning capabilities for Networks
  • Network configuration and optimization through Large GenAI models
  • Large GenAI models for resource allocation and quality of service optimization
  • Large GenAI models for network fault diagnosis and troubleshooting
  • LLMs for network performance prediction
  • LLMs for network protocol design
  • Scheduling and load balancing with LLMs
  • QoS/QoE prediction and optimization using LLMs
  • Natural Language Interfaces for Network Management
  • Using LLMs to generate network configurations from natural language
  • Troubleshooting and diagnostics through conversational interfaces
  • LLMs in Mobile and Wireless Networking
  • Adaptive LLMs for edge and mobile scenarios
  • LLMs for device mobility prediction and handover optimization
  • Federated learning with LLMs in wireless networks
  • LLMs and Network Data Analytics
  • Summarization of network incidents and logs via LLMs
  • Automated documentation and change logs using LLMs
  • Efficient fine-tuning and inference of LLMs in network environments
  • Deployment of LLMs at the edge, in routers, or programmable switches
  • LLMs for Emerging Network Architectures
  • Use of LLMs in Software-Defined Networking (SDN) and Network Function Virtualization (NFV)
  • LLMs for programmable networks and intent-based networking
  • LLM Applications in 6G, IoT, and space-terrestrial integrated networks
  • Datasets and benchmarks for evaluating LLMs in networking
  • Explainability and interpretability of LLMs in networking tasks
  • Human-in-the-loop evaluation frameworks
  • Multi-modal models for networking (e.g., combining text, telemetry, and packet traces)
  • Ethical considerations, fairness, and bias in LLM-driven network operations
  • LLMs for cybersecurity education and training in networked environments

Submission guidelines

Important dates

  • Paper Registration: Jun 08, 2026 (AoE)
  • Paper Submission Deadline: Jun 15, 2026 (AoE)
  • Paper Acceptance Notification: August 1, 2026
  • Camera-ready Papers Due: August 15, 2026

Special Track Organizers

Track Chairs

  • Suranga Seneviratne – The University of Sydney
  • Madhusanka Liyanage – University College Dublin

Publicity chiar

  • Fariza Rashid – The University of Sydney

Technical Program Committee (TBC)

  • Chamara Kattadige – RMIT University
  • Engin Zeydan – Centre Tecnològic de Telecomunicacions de Catalunya
  • Minzhao Lyu – The University of New South Wales
  • Shen Wang – University College of Dublin
  • Surangika Ranathunga  – Massey University
  • Gustavo Batista – The University of New South Wales
  • Ying Li – North China University of Technology
  • Salimur Choudhury – Queen’s University
  • Alessio Sacco – Politecnico Di Torino
  • Fariza Rashid – The University of Sydney
  • Abdelkader Lahmadi – Université de Lorraine

Past LLMNets