2 papers
cs.CV2024
DALDA: Data Augmentation Leveraging Diffusion Model and LLM with Adaptive Guidance Scaling
Kyuheon Jung, Yongdeuk Seo, Seongwoo Cho +3
In this paper, we present an effective data augmentation framework leveraging the Large Language Model (LLM) and Diffusion Model (DM) to tackle the challenges inherent in data-scar…
cs.CL2023
Pseudo Outlier Exposure for Out-of-Distribution Detection using Pretrained Transformers
Jaeyoung Kim, Kyuheon Jung, Dongbin Na +3
For real-world language applications, detecting an out-of-distribution (OOD) sample is helpful to alert users or reject such unreliable samples. However, modern over-parameterized…