5 citations · 6 across the 3 of their papers we have counts for
3 papers
cs.CL2023
Co-training and Co-distillation for Quality Improvement and Compression of Language Models
Hayeon Lee, Rui Hou, Jongpil Kim +4
Knowledge Distillation (KD) compresses computationally expensive pre-trained language models (PLMs) by transferring their knowledge to smaller models, allowing their use in resourc…
cs.CL2023★ 1 cited
A Study on Knowledge Distillation from Weak Teacher for Scaling Up Pre-trained Language Models
Hayeon Lee, Rui Hou, Jongpil Kim +3
Distillation from Weak Teacher (DWT) is a method of transferring knowledge from a smaller, weaker teacher model to a larger student model to improve its performance. Previous studi…
cs.CV2015★ 5 cited
Discovering Characteristic Landmarks on Ancient Coins using Convolutional Networks
Jongpil Kim, Vladimir Pavlovic
In this paper, we propose a novel method to find characteristic landmarks on ancient Roman imperial coins using deep convolutional neural network models (CNNs). We formulate an opt…