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cs.LG2026
Practical Scaling Laws: Converting Compute into Performance in a Data-Constrained World
Christopher M. Bryant, Hao Liu
The scaling laws guiding modern model training were calibrated for a single regime: data-rich, single-epoch pretraining. The dominant such scaling law form, Chinchilla's $L = E + A…
eess.SP2026
Inverse Design of Multi-Layer Sub-Pixel-Resolution RF Passives Through Grayscale Diffusion with Flexible S-Parameter Conditioning
Tommaso Dreossi, Christopher M. Bryant, Hao Liu +4
Inverse design of RF passive components from S-parameters is a high-dimensional, ill-posed problem, and prior generative approaches are limited to single-layer binary-metallization…