21 citations · 43 across the 5 of their papers we have counts for
5 papers
An Empirical Study of Invariant Risk Minimization
Yo Joong Choe, Jiyeon Ham, Kyubyong Park
Invariant risk minimization (IRM) (Arjovsky et al., 2019) is a recently proposed framework designed for learning predictors that are invariant to spurious correlations across diffe…
KorNLI and KorSTS: New Benchmark Datasets for Korean Natural Language Understanding
Jiyeon Ham, Yo Joong Choe, Kyubyong Park +2
Natural language inference (NLI) and semantic textual similarity (STS) are key tasks in natural language understanding (NLU). Although several benchmark datasets for those tasks ha…
Jejueo Datasets for Machine Translation and Speech Synthesis
Kyubyong Park, Yo Joong Choe, Jiyeon Ham
Jejueo was classified as critically endangered by UNESCO in 2010. Although diverse efforts to revitalize it have been made, there have been few computational approaches. Motivated…
A Neural Grammatical Error Correction System Built On Better Pre-training and Sequential Transfer Learning
Yo Joong Choe, Jiyeon Ham, Kyubyong Park +1
Grammatical error correction can be viewed as a low-resource sequence-to-sequence task, because publicly available parallel corpora are limited. To tackle this challenge, we first…
Predicting drug-target interaction using 3D structure-embedded graph representations from graph neural networks
Jaechang Lim, Seongok Ryu, Kyubyong Park +3
Accurate prediction of drug-target interaction (DTI) is essential for in silico drug design. For the purpose, we propose a novel approach for predicting DTI using a GNN that direct…