35 citations · 63 across the 8 of their papers we have counts for
9 papers
Enhancing Out-of-Distribution Detection in Natural Language Understanding via Implicit Layer Ensemble
Hyunsoo Cho, Choonghyun Park, Jaewook Kang +3
Out-of-distribution (OOD) detection aims to discern outliers from the intended data distribution, which is crucial to maintaining high reliability and a good user experience. Most…
Exploiting Session Information in BERT-based Session-aware Sequential Recommendation
Jinseok Seol, Youngrok Ko, Sang-goo Lee
In recommendation systems, utilizing the user interaction history as sequential information has resulted in great performance improvement. However, in many online services, user in…
Technologies for AI-Driven Fashion Social Networking Service with E-Commerce
Jinseok Seol, Seongjae Kim, Sungchan Park +7
The rapid growth of the online fashion market brought demands for innovative fashion services and commerce platforms. With the recent success of deep learning, many applications em…
IDS at SemEval-2020 Task 10: Does Pre-trained Language Model Know What to Emphasize?
Jaeyoul Shin, Taeuk Kim, Sang-goo Lee
We propose a novel method that enables us to determine words that deserve to be emphasized from written text in visual media, relying only on the information from the self-attentio…
Are Pre-trained Language Models Aware of Phrases? Simple but Strong Baselines for Grammar Induction
Taeuk Kim, Jihun Choi, Daniel Edmiston +1
With the recent success and popularity of pre-trained language models (LMs) in natural language processing, there has been a rise in efforts to understand their inner workings. In…
Variational Hierarchical Dialog Autoencoder for Dialog State Tracking Data Augmentation
Kang Min Yoo, Hanbit Lee, Franck Dernoncourt +3
Recent works have shown that generative data augmentation, where synthetic samples generated from deep generative models complement the training dataset, benefit NLP tasks. In this…