Call for Papers
Call for Papers
Call for Papers
Conference Dates: 26-29 May 2025
Workshop Day: 26 May 2025
Workshop Paper Submission Deadline: 31 March 2025 18 April 2025
Acceptance Notification: 2 May 2025
Final (Camera Ready) Submission: 9 May 2025
Artificial Intelligence (AI) has become a transformative force in communication networks, reshaping their design, management, and optimization. In several areas, these systems hold the promise of significantly enhancing service provisioning and network operations. However, the adoption of AI-based systems in the telecom domain has been relatively slow, with operators expressing skepticism about their use for automated network management. This hesitation stems from several key challenges: first, the reliability of these models must be thoroughly understood before they can be deployed in critical infrastructure. Second, the opaque nature of ML/AI models—stemming from a lack of transparency—complicates understanding their behavior and decisions, preventing operators from fully trusting and adopting them. To address these issues, the 2nd International Workshop on Trustworthy and Explainable Artificial Intelligence for Networks (TX4NETs) aims to serve as a collaborative platform to drive advancements in AI systems that are not only powerful but also reliable, interpretable, and aligned with the expectations of network operators.
The 2nd International Workshop on Trustworthy and Explainable Artificial Intelligence for Networks seeks to bring together leading researchers, practitioners, and industry experts to delve into the latest advancements in AI and their applications in communication networks. The workshop will center on the foundational pillars of trustworthy AI, including transparency, robustness, reliability, adaptability, security, data privacy, and computational efficiency, with a focus on their implications for automating and optimizing network operations. Participants will engage in discussions around innovative techniques and methodologies that foster trustworthiness to address challenges in creating AI-driven network systems that inspire confidence.
Trustworthy AI for communication networks
Trustworthy AI for network management
Trustworthy AI for network security
XAI for trustworthy AI in networks
Reliability and robustness of AI models for Networks
Human-in-the-Loop systems for AI in communication networks
Fair resource allocation in communication networks
Privacy, security, robustness and reliability of AI for networks
XAI in networking
XAI for enhancing trustworthiness of AI in networks
XAI-driven network performance optimization
XAI for the Edge/Cloud and Internet-of-Things
XAI for network security, privacy, resilience and reliability
XAI for federated learning-based solutions of 5G/6G and future networks
XAI for digital twin-based solutions of 5G/6G and future networks
Case studies and deployments of XAI in communication networks
Explainable generative AI for networks
Explainable Reinforcement Learning in communication networks
Causal machine learning for networking
Ethical Considerations in AI for communication networks
Interoperability and standards in AI for communication networks
Regulatory landscape for AI in communication networks
Authors are invited to submit original contributions that have neither been published nor submitted for publication elsewhere. Papers should be prepared using the IEEE double-column conference style (10pt font) and are limited to 6 pages including references.
Papers must be submitted electronically in PDF format through EDAS (link to edas).
All papers will be peer reviewed, and the comments will be provided to the authors. Once accepted, the paper will be included in the conference proceedings and will be eligible for submission to the IEEE Xplore Digital Library.
At least one author of each accepted paper is required to register and present the work in the workshop.