The 2nd Workshop on Next-Gen Networks through LLMs, Action Models, and Multi-Agent Systems

Workshop Organizers:

Dr. Pengfei Wang
Dalian University of Technology, Dalian, China
Email: wangpf@dlut.edu.cn

Dr. Leyou Yang
Nanjing University of Information Science and Technology, Nanjing, China
Email: leyou.yang@nuist.edu.cn

Short Biography of Organizers:

Pengfei Wang (Member, IEEE) received the B.S., M.S., and Ph.D. degrees in software engineering from Northeastern University (NEU), China, in 2013, 2015, and 2020, respectively. From 2016 to 2018, he was a Visiting Ph.D. Student with the Department of Electrical Engineering and Computer Science, Northwestern University, Evanston, IL, USA. He is currently an Associate Professor with the School of Computer Science and Technology, Dalian University of Technology (DUT), China. He has authored more than 60 papers on high-quality journals and conferences, such as IEEE Transactions on Mobile Computing, IEEE/ACM Transactions on Networking, IEEE Journal on Selected Areas in Communications, IEEE Transactions on Services Computing, IEEE Transactions on Wireless Communications, IEEE Transactions on Intelligent Transportation Systems, ACM TOSN, IEEE Transactions on Network Science and Engineering, IEEE INFOCOM, IEEE ICNP, and IEEE ICDCS. He also holds a series of patents in USA and China. His research interests include distributed artificial intelligence, computer networks, and the IoT.

 

Leyou Yang received the Ph.D. degree from Northeastern University (China). From 2021 to 2022, he was a visiting Ph.D. student at the School of Computer Science and Engineering, Nanyang Technological University, Singapore. He is currently a Lecturer at the School of Computer Science, Nanjing University of Information Science and Technology. He has authored over 20 papers in prestigious journals and conferences, including IEEE Transactions on Mobile Computing and IEEE INFOCOM. His research interests span wireless communications, edge computing, federated learning, reinforcement learning, and resource allocation.

 

A Brief Description of Workshop:

       The emergence of large language models (LLMs) and generative artificial intelligence (GenAI) has introduced unprecedented capabilities in processing vast amounts of data and generating contextually accurate responses, paving the way for new methodologies across various industries. This trend has given rise to large action models (LAMs), which build upon the principles of large-scale generative language models to analyze extensive datasets and make complex decisions in real time. Unlike traditional AI models that rely on predefined outcomes, LAMs leverage the adaptive learning capabilities of generative AI to evaluate a wide range of possible outcomes and choose the most suitable action based on the given context, rendering them particularly appealing for dynamic environments where conditions frequently change. The telecommunications industry stands to benefit significantly from LAMs in realizing automation and enhancing network performance; however, given the complex and distributed nature of Telecom networks, we anticipate that the deployment of LAMs in this context will be realized through the development of multi-agent systems, where multiple LAMs interact and cooperate within a shared environment to enable more sophisticated and coordinated decision-making processes—ultimately paving the way toward intelligently native autonomous networks and, in the long term, artificial general intelligence (AGI). It is in this context that our workshop, "Next-Gen Networks through LLMs, Action Models, and Multi-Agent Systems," is organized in conjunction with the International Conference on Mobility, Sensing and Networking (MSN 2026). The workshop directly complements MSN's emerging focus on Agentic Systems and LLMs for mobility, sensing, and networking, by offering a dedicated, in-depth exploration of the specific paradigm shift introduced by LAMs and multi-agent systems. The workshop will be structured as a half-day session featuring peer-reviewed paper presentations and a panel discussion to foster interactive dialogue on the roadmap toward fully autonomous, AI-native networks. All accepted papers will be published in the MSN 2026 proceedings, and the workshop will be actively promoted through academic networks, social media, and targeted mailing lists to attract a diverse audience of researchers and practitioners, with the aim of advancing research in the emerging field of large-scale generative models for Telecom networks and exploring the opportunities, challenges, and future directions for leveraging these powerful models in wireless communications.

Paper Submission Guidelines:

       All submissions should follow the IEEE 8.5″x 11″Two-Column Format. Each submission can have up to 6 pages. Authors of accepted papers are expected to present their papers at the workshop. All submissions to MSN 2026 must be uploaded to EasyChair: https://easychair.org/conferences/?conf=msn2026

Important Dates:

• Sep. 20, 2026

  Paper Submission

• Oct. 30, 2026

  Author Notification

• Nov. 7, 2024

  Camera-ready

• Dec. 18-20, 2024

  Conference Date