arXiv:2604.02196v1 Announce Type: cross
Abstract: Many communication and control problems are cast as multi-objective Markov decision processes (MOMDPs). The complete solution to an MOMDP is the Pareto front. Much of the literature approximates this f…
arXiv:2601.18242v2 Announce Type: replace
Abstract: Accurate radio-frequency (RF) material parameters are essential for electromagnetic digital twins in 6G systems, yet gradient-based inverse ray tracing (RT) remains sensitive to initialization and co…
arXiv:2604.00189v1 Announce Type: cross
Abstract: To support practitioners in understanding how agentic systems are designed in real-world industrial practice, we present a review of practitioner conference talks on AI agents. We analyzed 138 recorded…
arXiv:2604.01049v1 Announce Type: cross
Abstract: Next-generation (NextG) cellular networks are designed to support emerging applications with diverse data rate and latency requirements, such as immersive multimedia services and large-scale Internet o…
arXiv:2603.16949v2 Announce Type: replace-cross
Abstract: Mobile Edge Computing (MEC) technology has been introduced to enable could computing at the edge of the network in order to help resource limited mobile devices with time sensitive data process…
arXiv:2603.29426v1 Announce Type: cross
Abstract: In recent years, advances in underwater networking and multi-agent reinforcement learning (MARL) have significantly expanded multi-autonomous underwater vehicle (AUV) applications in marine exploration…
arXiv:2603.29520v1 Announce Type: cross
Abstract: Encrypted traffic classification is a critical task for network security. While deep learning has advanced this field, the occlusion of payload semantics by encryption severely challenges standard mode…
arXiv:2603.29537v1 Announce Type: cross
Abstract: Network traffic classification using self-supervised pre-training models based on Masked Autoencoders (MAE) has demonstrated a huge potential. However, existing methods are confined to isolated byte-le…
arXiv:2603.29656v1 Announce Type: cross
Abstract: Autonomous 6G network management requires agents that can execute tools, observe the resulting state changes, and adapt their decisions accordingly. Existing benchmarks based on static questions or scr…
arXiv:2306.05494v5 Announce Type: replace-cross
Abstract: Machine Learning (ML) has become pervasive, and its deployment in Network Intrusion Detection Systems (NIDS) is inevitable due to its automated nature and high accuracy compared to traditional …