2 papers
cs.AR2026
Unveiling the Potential of Quantization with MXFP4: Strategies for Quantization Error Reduction
Jatin Chhugani, Geonhwa Jeong, Bor-Yiing Su +8
Large Language Models (LLMs) have intensified the need for low-precision formats that enable efficient, large-scale inference. The Open Compute Project (OCP) Microscaling (MX) stan…
cs.LG2025
MoR: Mixture Of Representations For Mixed-Precision Training
Bor-Yiing Su, Peter Dykas, Mike Chrzanowski +1
Mixed-precision training is a crucial technique for scaling deep learning models, but successful mixedprecision training requires identifying and applying the right combination of…