InfLLM: Training-Free Long-Context Extrapolation for LLMs with an Efficient Context Memory

1 code implementation • 7 Feb 2024 • Chaojun Xiao, Pengle Zhang, Xu Han, Guangxuan Xiao, Yankai Lin, Zhengyan Zhang, Zhiyuan Liu, Maosong Sun

In this paper, we unveil the intrinsic capacity of LLMs for understanding extremely long sequences without any fine-tuning.

Variator: Accelerating Pre-trained Models with Plug-and-Play Compression Modules

1 code implementation • 24 Oct 2023 • Chaojun Xiao, Yuqi Luo, Wenbin Zhang, Pengle Zhang, Xu Han, Yankai Lin, Zhengyan Zhang, Ruobing Xie, Zhiyuan Liu, Maosong Sun, Jie zhou

Pre-trained language models (PLMs) have achieved remarkable results on NLP tasks but at the expense of huge parameter sizes and the consequent computational costs.

Computational Efficiency