3 papers indexed
Yilong Liu, Xi Yang, Jing Xu, Jun Zhang, Shi jin
Extremely large-scale multiple-input multiple-output (XL-MIMO) is crucial for next-generation communication systems. In practice, the deployment of non-square uniform planar arrays (UPAs) fundamentally alters wavefront characteristics and induces anisotropic beamfocusing capabili…
Xu Yang, Mingyang Yu, Jing Xu, Keqian Li
Physics-informed neural networks (PINNs) are unusually sensitive to interacting choices of architecture, activation, loss weighting, collocation, optimization, and constraint enforcement. Large language models (LLMs) can propose these choices, but independent recommendations do n…
Zaiwen Yang, Huaqing Zhang, Jing Xu, Jingzhao Zhang
Learning-rate transfer can reduce the cost of training large language models: instead of sweeping learning rates at target scale, practitioners extrapolate from smaller runs. Existing approaches often assume that the optimal learning rate follows a log-linear scaling law in data…