Aim and Scope
The GenXNet Workshop fosters research on Generative AI (GenAI) and eXplainable AI (XAI) within Networking, focusing on challenges, applications, and future directions (e.g. 6G scenarios).
GenAI is emerging as an effective instrument for generating complex human-like text, dynamic interaction, and advanced comprehension. Large Language Models (LLMs) are widespread across diverse applications, but their interplay with networking aspects is in its early stages. Recent advances indicate strong potential in revolutionizing networking-related tasks, such as traffic generation, anomaly detection, cybersecurity, log analysis, and automated network management.
In addition, AI-driven solutions in critical networking environments pose new challenges, particularly due to their black-box nature, raising concerns about trust, interpretability, and transparency. XAI plays a pivotal role in addressing these concerns, offering methods to interpret, validate, and debug AI-driven networking solutions. By enhancing transparency and reliability, XAI fosters accountability, security, and regulatory compliance, ensuring that AI can be safely and effectively deployed in networking environments, especially in future 6G network environments.
The GenXNet workshop aims to bring together researchers and practitioners to explore the interplay between GenAI and Explainability with wired and wireless Internet, focusing on the unique opportunities and challenges posed by the next-generation 6G systems.
We welcome contributions that explore the impact of GenAI in networking as well as research on XAI applied to AI-driven networking solutions. While contributions that integrate both GenAI and XAI are highly encouraged, submissions may focus on either GenAI or XAI, provided they maintain a strong connection to networking applications, with particular interest in scenarios relevant to future 6G networks.
