8 citations · 30 across the 23 of their papers we have counts for
Showing 2022Show all
3 papers · 1 filter
cs.CL2022
A Data Cartography based MixUp for Pre-trained Language Models
Seo Yeon Park, Cornelia Caragea
MixUp is a data augmentation strategy where additional samples are generated during training by combining random pairs of training samples and their labels. However, selecting rand…
cs.CL2022
On the Calibration of Pre-trained Language Models using Mixup Guided by Area Under the Margin and Saliency
Seo Yeon Park, Cornelia Caragea
A well-calibrated neural model produces confidence (probability outputs) closely approximated by the expected accuracy. While prior studies have shown that mixup training as a data…
cs.LG2022★ 8 cited
Lipschitz-constrained Unsupervised Skill Discovery
Seohong Park, Jongwook Choi, Jaekyeom Kim +2
We study the problem of unsupervised skill discovery, whose goal is to learn a set of diverse and useful skills with no external reward. There have been a number of skill discovery…