2 citations · 3 across the 2 of their papers we have counts for
2 papers
cs.CL2024★ 1 cited
Efficient Continual Pre-training by Mitigating the Stability Gap
Yiduo Guo, Jie Fu, Huishuai Zhang +2
Continual pre-training has increasingly become the predominant approach for adapting Large Language Models (LLMs) to new domains. This process involves updating the pre-trained LLM…
cs.CL2024★ 2 cited
Stacking Your Transformers: A Closer Look at Model Growth for Efficient LLM Pre-Training
Wenyu Du, Tongxu Luo, Zihan Qiu +5
LLMs are computationally expensive to pre-train due to their large scale. Model growth emerges as a promising approach by leveraging smaller models to accelerate the training of la…