42 citations · 71 across the 3 of their papers we have counts for
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cs.LG2025
An Empirical Study of Qwen3 Quantization
Xingyu Zheng, Yuye Li, Haoran Chu +7
The Qwen series has emerged as a leading family of open-source Large Language Models (LLMs), demonstrating remarkable capabilities in natural language understanding tasks. With the…
cs.LG2024★ 29 cited
An empirical study of LLaMA3 quantization: from LLMs to MLLMs
Wei Huang, Xingyu Zheng, Xudong Ma +7
The LLaMA family, a collection of foundation language models ranging from 7B to 65B parameters, has become one of the most powerful open-source large language models (LLMs) and the…
cs.LG2024★ 42 cited
Accurate LoRA-Finetuning Quantization of LLMs via Information Retention
Haotong Qin, Xudong Ma, Xingyu Zheng +6
The LoRA-finetuning quantization of LLMs has been extensively studied to obtain accurate yet compact LLMs for deployment on resource-constrained hardware. However, existing methods…