3 papers
cs.LG2026
LoPRo: Enhancing Low-Rank Quantization via Permuted Block-Wise Rotation
Hongyaoxing Gu, Lijuan Hu, Liye Yu +2
Post-training quantization (PTQ) enables effective model compression while preserving relatively high accuracy. Current weight-only PTQ methods primarily focus on the challenging s…
cs.LG2026
FLRQ: Faster LLM Quantization with Flexible Low-Rank Matrix Sketching
Hongyaoxing Gul, Lijuan Hu, Shuzi Niu +1
Traditional post-training quantization (PTQ) is considered an effective approach to reduce model size and accelerate inference of large-scale language models (LLMs). However, exist…
quant-ph2025
Identify and Quantify Various Dissipation Mechanisms of Josephson Junction in Superconducting Circuits
Hao Deng, Huijuan Zhan, Lijuan Hu +12
Pinpointing the dissipation mechanisms and evaluating their impacts to the performance of Josephson junction (JJ) are crucial for its application in superconducting circuits. In th…