works on
additive-multiplicative updates 1large language models 1low-precision training 1optimizer design 1quantized neural networks 1

From the 1 of 1 linked paper with an AI index.

collaborators

1 paper

cs.LG2026

M+Adam: Low-Precision Training via Additive-Multiplicative Optimization

Xiaoyuan Liang, Sebastian Loeschcke, Mads Toftrup +1

The paper introduces M+Adam, an optimizer that blends additive and multiplicative updates to enable stable low‑precision training of large language models without keeping high‑prec…