5 papers · 1 filter
VolDoGer: LLM-assisted Datasets for Domain Generalization in Vision-Language Tasks
Juhwan Choi, Junehyoung Kwon, JungMin Yun +2
Domain generalizability is a crucial aspect of a deep learning model since it determines the capability of the model to perform well on data from unseen domains. However, research…
Making Sense of Korean Sentences: A Comprehensive Evaluation of LLMs through KoSEnd Dataset
Seunguk Yu, Kyeonghyun Kim, Jungmin Yun +1
Although LLMs have made significant progress in various languages, there are still concerns about their effectiveness with low-resource agglutinative languages compared to language…
Multi-News+: Cost-efficient Dataset Cleansing via LLM-based Data Annotation
Juhwan Choi, Jungmin Yun, Kyohoon Jin +1
The quality of the dataset is crucial for ensuring optimal performance and reliability of downstream task models. However, datasets often contain noisy data inadvertently included…
UniGen: Universal Domain Generalization for Sentiment Classification via Zero-shot Dataset Generation
Juhwan Choi, Yeonghwa Kim, Seunguk Yu +2
Although pre-trained language models have exhibited great flexibility and versatility with prompt-based few-shot learning, they suffer from the extensive parameter size and limited…
Focus on the Core: Efficient Attention via Pruned Token Compression for Document Classification
Jungmin Yun, Mihyeon Kim, Youngbin Kim
Transformer-based models have achieved dominant performance in numerous NLP tasks. Despite their remarkable successes, pre-trained transformers such as BERT suffer from a computati…