arXiv Machine Learning

Multi-perspective Imbalance-Conscious 6G Beamforming Optimization and Performance

arXiv:2608. 12929v1 Announce Type: new Abstract: The study presents a systematic machine learning (ML) study of 6G-IoT beamforming optimization (6GBO) using supervised and unsupervised approaches.

arXiv AI

Jul 14

JEPA for AI-Native 6G: Predictive Representations and Open Challenges

arXiv:2607. 09798v1 Announce Type: cross Abstract: Sixth-generation (6G) networks are moving toward AI-native operation, where learning modules are embedded across the radio access network (RAN), edge, and core.

By Sheikh Salman Hassan, Irshad A. Meer, Almoatssimbillah Saifaldawla, Yan Kyaw Tun, Mustafa Ozger, Madyan Alsenwi, Nguyen Van Huynh, Woong-Hee Lee, Cedomir Stefanovic, Mathini Sellathurai, Henk Wymeersch, Tharmalingam Ratnarajah

rag diffusion benchmarks

arXiv AI

1d ago

A Comprehensive Survey of Wireless Foundation Models for AI-Native 6G Networks

arXiv:2608. 14694v1 Announce Type: new Abstract: Foundation models are emerging as a transformative paradigm for AI-native sixth-generation (6G) wireless networks by enabling scalable, transferable, and data-efficient intelligence across diverse communication tasks.

By Naveed Khan, Besan Al Sbeihi, Maryam Alshehhi, Nasir Saeed

efficiency benchmarks safety

arXiv Machine Learning

Jul 22

Unsupervised Multi-kernel Learning for Automated Algorithm Selection

arXiv:2607. 19031v1 Announce Type: new Abstract: Automated algorithm selection in black-box optimization typically relies on supervised models that map landscape features to algorithm performance labels.

By Yihang Lu, Tome Eftimov, Carola Doerr

benchmarks

arXiv AI

Jun 3

WISE-HAR: A Generalizable Ensemble Deep Learning Framework for WiFi-Based Human Activity Recognition

arXiv:2606. 02974v1 Announce Type: new Abstract: Human Activity Recognition (HAR) using WiFi signals has emerged as a transformative technology for smart homes, healthcare monitoring, security systems, and ambient assisted living.

By Maheen Arshad, Qindeel E Zahra, Muhammad Khuram Shahzad

safety

arXiv AI

Jul 2

Cross-Domain Generalization Failure in Lightweight Intrusion Detection Models for IIoT Networks

arXiv:2607. 00553v1 Announce Type: cross Abstract: Lightweight machine learning models are increasingly proposed for intrusion detection in Industrial Internet of Things (IIoT) networks due to their suitability for resource-constrained edge deployment.

By MD Azizul Hakim, Md Shihab Uddin, Talha Ibne Anis

efficiency safety

arXiv Machine Learning

Aug 4

Cluster-Aware Over-the-Air Federated Learning with Energy-Harvesting Devices: From Global Training to Model Personalization

arXiv:2608. 01426v1 Announce Type: new Abstract: Federated learning (FL) enables distributed optimization and learning across decentralized edge devices while preserving data privacy, but its performance is fundamentally constrained by heterogeneous data distributions, limited communication resources, and energy availability.

By Furkan Bagci, Busra Tegin, Mohammad Kazemi, Tolga M. Duman

safety

arXiv Machine Learning

Jul 15

A Comprehensive Evaluation of Deep Learning Object Detection Models on Heterogeneous Edge Devices

arXiv:2409. 16808v3 Announce Type: replace-cross Abstract: Modern applications such as autonomous vehicles, intelligent surveillance, and smart city systems increasingly require object detection on resource-constrained edge devices.

By Daghash K. Alqahtani, Muhammad Aamir Cheema, Maria A. Rodriguez, Adel N. Toosi

agents computer-vision benchmarks

arXiv Machine Learning

Jul 7

F-ACVAE: A Federated Adaptive Conditional Variational Auto-Encoder for Privacy-Preserving Intrusion Detection in IoT Networks

arXiv:2607. 04698v1 Announce Type: new Abstract: The rapid proliferation of Internet of things (IoT) devices has significantly expanded the cyber-attack surface, necessitating robust and privacy-preserving intrusion detection systems (IDS).

By Mohammad Ansarimehr, Somayeh Changiz, Ehsan Baghishani, Ali Mousavi

benchmarks safety

arXiv AI

1d ago

CM-MAE: A Physics-Guided Cross-Modal Self-Supervised Learning Framework for Vision-Wireless Applications

arXiv:2608. 15972v1 Announce Type: cross Abstract: Synchronized camera and wireless measurements observe the same scene through different physical channels.

By Yubo Zhang, Yiyao Liu

fine-tuning multimodal safety

arXiv Machine Learning

Jul 23

Self-organizing Architecture of Receptron Units: a Hardware-Aware Framework for Edge Intelligence

arXiv:2607. 20162v1 Announce Type: new Abstract: The growing demand for intelligent processing at the edge of IoT networks is constrained by the severe computational and memory limitations of microcontroller units, which render impractical conventional deep learning approaches.

By Stefano Radice, Ludovico Casaccia, Riccaro Emanuele Beccalli, Bruno Paroli, Paolo Milani

benchmarks

arXiv Machine Learning

Aug 6

FM4WiFi: Flow Matching for Multi-AP Coordination in Dense Deployments of Beyond Wi-Fi 8 Networks

arXiv:2608. 04050v1 Announce Type: cross Abstract: Wi-Fi networks are moving beyond random channel access toward tightly coordinated operation across access points (APs), a shift reflected in Wi-Fi 8's multi-AP coordination (MAPC).

By Maksymilian Wojnar, Krzysztof Rusek, Katarzyna Kosek-Szott, Szymon Szott

diffusion benchmarks

arXiv AI

Jun 9

HASA: Subnet Allocation for Compute-Constrained Model-Heterogeneous Federated Learning

arXiv:2606. 07621v1 Announce Type: cross Abstract: Edge services increasingly use federated learning to personalize on-device models while keeping sensitive data local.

By Amir Hossein Shahdadian, Ahmed M. Abdelmoniem, Mahdi Taheri, Samira Nazari, Christian Herglotz

benchmarks

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