1 citations · 2 across the 5 of their papers we have counts for
5 papers
SUMMPILOT: Bridging Efficiency and Customization for Interactive Summarization System
JungMin Yun, Juhwan Choi, Kyohoon Jin +3
This paper incorporates the efficiency of automatic summarization and addresses the challenge of generating personalized summaries tailored to individual users' interests and requi…
CoBA: Counterbias Text Augmentation for Mitigating Various Spurious Correlations via Semantic Triples
Kyohoon Jin, Juhwan Choi, Jungmin Yun +3
Deep learning models often learn and exploit spurious correlations in training data, using these non-target features to inform their predictions. Such reliance leads to performance…
SoftEDA: Rethinking Rule-Based Data Augmentation with Soft Labels
Juhwan Choi, Kyohoon Jin, Junho Lee +2
Rule-based text data augmentation is widely used for NLP tasks due to its simplicity. However, this method can potentially damage the original meaning of the text, ultimately hurti…
AutoAugment Is What You Need: Enhancing Rule-based Augmentation Methods in Low-resource Regimes
Juhwan Choi, Kyohoon Jin, Junho Lee +2
Text data augmentation is a complex problem due to the discrete nature of sentences. Although rule-based augmentation methods are widely adopted in real-world applications because…
GPTs Are Multilingual Annotators for Sequence Generation Tasks
Juhwan Choi, Eunju Lee, Kyohoon Jin +1
Data annotation is an essential step for constructing new datasets. However, the conventional approach of data annotation through crowdsourcing is both time-consuming and expensive…