activity
20232026
most citedHow Do Large Language Models Acquire Factual Knowledge During Pretraining?

3 citations · 3 across the 7 of their papers we have counts for

collaborators
Showing 2023Show all

1 paper · 1 filter

cs.CL2023

NASH: A Simple Unified Framework of Structured Pruning for Accelerating Encoder-Decoder Language Models

Jongwoo Ko, Seungjoon Park, Yujin Kim +4

Structured pruning methods have proven effective in reducing the model size and accelerating inference speed in various network architectures such as Transformers. Despite the vers…