2 papers
cs.LG2025
FlexQuant: A Flexible and Efficient Dynamic Precision Switching Framework for LLM Quantization
Fangxin Liu, Zongwu Wang, JinHong Xia +6
The rapid advancement of large language models (LLMs) has exacerbated the memory bottleneck due to the widening gap between model parameter scaling and hardware capabilities. While…
cs.LG2025
LCD: Advancing Extreme Low-Bit Clustering for Large Language Models via Knowledge Distillation
Fangxin Liu, Ning Yang, Junping Zhao +3
Large language models (LLMs) have achieved significant progress in natural language processing but face challenges in deployment due to high memory and computational requirements.…