From the 1 of 2 linked papers with an AI index.
2 papers
cs.LG2026
Self-Evolving In-Context Learning for Direct Pilot-to-Beamformer Design in MU-MISO Systems
Yubo Zhang, Xiaodong Wang
The paper proposes an in-context learning framework using a Transformer backbone to design pilot-to-beamformer mappings for multi-user MISO systems, enabling rapid adaptation to va…
cs.LG2026
A Semi-amortized Lifted Learning-to-Optimize Masked (SALLO-M) Transformer Model for Scalable and Generalizable Beamforming
Yubo Zhang, Xiao-Yang Liu, Xiaodong Wang
We develop an unsupervised deep learning framework for real-time scalable and generalizable downlink beamforming in multi-user multiple-input single-output (MU-MISO) systems. The p…