17 citations · 18 across the 8 of their papers we have counts for
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cs.CL2024
First Activations Matter: Training-Free Methods for Dynamic Activation in Large Language Models
Chi Ma, Mincong Huang, Ying Zhang +5
Dynamic activation (DA) techniques, such as DejaVu and MoEfication, have demonstrated their potential to significantly enhance the inference efficiency of large language models (LL…
cs.LG2024★ 1 cited
QQQ: Quality Quattuor-Bit Quantization for Large Language Models
Ying Zhang, Peng Zhang, Mincong Huang +7
Quantization is a proven effective method for compressing large language models. Although popular techniques like W8A8 and W4A16 effectively maintain model performance, they often…
cs.CV2024
QuantTune: Optimizing Model Quantization with Adaptive Outlier-Driven Fine Tuning
Jiun-Man Chen, Yu-Hsuan Chao, Yu-Jie Wang +3
Transformer-based models have gained widespread popularity in both the computer vision (CV) and natural language processing (NLP) fields. However, significant challenges arise duri…