29 citations · 49 across the 6 of their papers we have counts for
13 papers
False Negative Distillation and Contrastive Learning for Personalized Outfit Recommendation
Seongjae Kim, Jinseok Seol, Holim Lim +1
Personalized outfit recommendation has recently been in the spotlight with the rapid growth of the online fashion industry. However, recommending outfits has two significant challe…
Self-Guided Contrastive Learning for BERT Sentence Representations
Taeuk Kim, Kang Min Yoo, Sang-goo Lee
Although BERT and its variants have reshaped the NLP landscape, it still remains unclear how best to derive sentence embeddings from such pre-trained Transformers. In this work, we…
Contrastive Learning for Unsupervised Image-to-Image Translation
Hanbit Lee, Jinseok Seol, Sang-goo Lee
Image-to-image translation aims to learn a mapping between different groups of visually distinguishable images. While recent methods have shown impressive ability to change even in…
Semantics-Preserving Adversarial Training
Wonseok Lee, Hanbit Lee, Sang-goo Lee
Adversarial training is a defense technique that improves adversarial robustness of a deep neural network (DNN) by including adversarial examples in the training data. In this pape…
SNU_IDS at SemEval-2019 Task 3: Addressing Training-Test Class Distribution Mismatch in Conversational Classification
Sanghwan Bae, Jihun Choi, Sang-goo Lee
We present several techniques to tackle the mismatch in class distributions between training and test data in the Contextual Emotion Detection task of SemEval 2019, by extending th…
Data Augmentation for Spoken Language Understanding via Joint Variational Generation
Kang Min Yoo, Youhyun Shin, Sang-goo Lee
Data scarcity is one of the main obstacles of domain adaptation in spoken language understanding (SLU) due to the high cost of creating manually tagged SLU datasets. Recent works i…