4 citations · 5 across the 2 of their papers we have counts for
2 papers
cs.CV2021★ 1 cited
Self-Distilled Self-Supervised Representation Learning
Jiho Jang, Seonhoon Kim, Kiyoon Yoo +3
State-of-the-art frameworks in self-supervised learning have recently shown that fully utilizing transformer-based models can lead to performance boost compared to conventional CNN…
cs.CL2021★ 4 cited
What Changes Can Large-scale Language Models Bring? Intensive Study on HyperCLOVA: Billions-scale Korean Generative Pretrained Transformers
Boseop Kim, HyoungSeok Kim, Sang-Woo Lee +34
GPT-3 shows remarkable in-context learning ability of large-scale language models (LMs) trained on hundreds of billion scale data. Here we address some remaining issues less report…