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From the 1 of 9 linked papers with an AI index.

collaborators

9 papers

cs.AI2026

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…

eess.SP2026

CSI-CLIP++: A Scalable Channel Foundation Model for Wireless Communication via CIR-CSI Consistency

Jun Jiang, Wenjun Yu, Yunfan Li +2

Self-supervised learning can exploit large-scale unlabeled channel data to improve the transferability of wireless AI models. Existing channel foundation models are often built on…

eess.SP2026

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…

eess.SP2026

Dynamic Channel Charting: An LSTM-AE-based Approach

Yuan Gao, Wenjing Xie, Yiming Liu +3

With the development of the sixth-generation (6G) communication system, Channel State Information (CSI) plays a crucial role in improving network performance. Traditional Channel C…

cs.CV2026

Efficient UAV trajectory prediction: A multi-modal deep diffusion framework

Yuan Gao, Xinyu Guo, Wenjing Xie +4

To meet the requirements for managing unauthorized UAVs in the low-altitude economy, a multi-modal UAV trajectory prediction method based on the fusion of LiDAR and millimeter-wave…

cs.CV2025

Great X: A Unified Multi-Modal Simulator Bridging the Sim2Real Gap for 6G

Kongwu Huang, Shiyi Mu, Jun Jiang +2

Large-scale, precisely synchronized multi-modal datasets are critical for data-driven sixth-generation (6G) wireless research, yet real-world collection remains costly and difficul…