32 citations · 32 across the 2 of their papers we have counts for
2 papers
cs.CL2022★ 32 cited
Can Large Language Models Truly Understand Prompts? A Case Study with Negated Prompts
Joel Jang, Seonghyeon Ye, Minjoon Seo
Previous work has shown that there exists a scaling law between the size of Language Models (LMs) and their zero-shot performance on different downstream NLP tasks. In this work, w…
cs.CL2021
Efficient Contrastive Learning via Novel Data Augmentation and Curriculum Learning
Seonghyeon Ye, Jiseon Kim, Alice Oh
We introduce EfficientCL, a memory-efficient continual pretraining method that applies contrastive learning with novel data augmentation and curriculum learning. For data augmentat…