activity
20232026
most citedOWQ: Outlier-Aware Weight Quantization for Efficient Fine-Tuning and Inference of Large Language Models

8 citations · 10 across the 7 of their papers we have counts for

collaborators
Showing cs.LGShow all

1 paper · 1 filter

cs.LG2025

AMQ: Enabling AutoML for Mixed-precision Weight-Only Quantization of Large Language Models

Sangjun Lee, Seung-taek Woo, Jungyu Jin +2

To enable broader deployment of Large Language Models (LLMs), it is essential to identify the best-performing model under strict memory constraints. We present AMQ, Automated Mixed…