17 citations · 17 across the 8 of their papers we have counts for
4 papers · 1 filter
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…
MOYU: A Theoretical Study on Massive Over-activation Yielded Uplifts in LLMs
Chi Ma, Mincong Huang, Chao Wang +2
Massive Over-activation Yielded Uplifts(MOYU) is an inherent property of large language models, and dynamic activation(DA) based on the MOYU property is a clever yet under-explored…
Dynamic Activation Pitfalls in LLaMA Models: An Empirical Study
Chi Ma, Mincong Huang, Chao Wang +2
In this work, we systematically investigate the efficacy of dynamic activation mechanisms within the LLaMA family of language models. Despite the potential of dynamic activation me…
Re-evaluating the Memory-balanced Pipeline Parallelism: BPipe
Mincong Huang, Chao Wang, Chi Ma +3
Pipeline parallelism is an essential technique in the training of large-scale Transformer models. However, it suffers from imbalanced memory consumption, leading to insufficient me…