12 papers
JEPA-CFM: A Joint Embedding Predictive Architecture-based Channel Foundation Model for Robust Fluid Antenna Systems
Yuan Gao, Yiming Liu, Jun Jiang +4
Fluid antenna systems (FAS) have emerged as a promising technology for sixth-generation (6G) wireless networks. By allowing antenna elements to move freely within a compact region,…
CFM-Bench: A Unified Multi-Domain, Multi-Task Benchmark for Channel Foundation Models
Yuan Gao, Wenjun Yu, Jun Jiang +3
The paper introduces CFM-Bench, a unified benchmark that evaluates channel foundation models across multiple wireless domains, tasks, and data configurations, enabling fair compari…
Towards channel foundation models (CFMs): Motivations, methodologies and opportunities
Jun Jiang, Yuan Gao, Xinyi Wu +1
Artificial intelligence (AI) has emerged as a pivotal enabler for next-generation wireless communication systems. However, conventional AI-based models encounter several limitation…
AI/ML for mobile networks: Current status in Rel. 19 and challenges ahead
Yuan Gao, Xinyi Wu, Jun Jiang +6
The transformative power of artificial intelligence (AI) and machine learning (ML) is recognized as a key enabler for sixth generation (6G) mobile networks by both academia and ind…
ReinPath: A Multimodal Reinforcement Learning Approach for Pathology
Kangcheng Zhou, Jun Jiang, Qing Zhang +3
Interpretability is significant in computational pathology, leading to the development of multimodal information integration from histopathological image and corresponding text dat…
CSI-MAE: A Masked Autoencoder-based Channel Foundation Model
Jun Jiang, Xiaolong Ruan, Shugong Xu
Self-Supervised Learning (SSL) has emerged as a key technique in machine learning, tackling challenges such as limited labeled data, high annotation costs, and variable wireless ch…