6 citations · 12 across the 12 of their papers we have counts for
5 papers · 1 filter
Multi-Architecture Multi-Expert Diffusion Models
Yunsung Lee, Jin-Young Kim, Hyojun Go +3
In this paper, we address the performance degradation of efficient diffusion models by introducing Multi-architecturE Multi-Expert diffusion models (MEME). We identify the need for…
ScoreCL: Augmentation-Adaptive Contrastive Learning via Score-Matching Function
Jin-Young Kim, Soonwoo Kwon, Hyojun Go +3
Self-supervised contrastive learning (CL) has achieved state-of-the-art performance in representation learning by minimizing the distance between positive pairs while maximizing th…
Addressing Negative Transfer in Diffusion Models
Hyojun Go, JinYoung Kim, Yunsung Lee +4
Diffusion-based generative models have achieved remarkable success in various domains. It trains a shared model on denoising tasks that encompass different noise levels simultaneou…
Cross Encoding as Augmentation: Towards Effective Educational Text Classification
Hyun Seung Lee, Seungtaek Choi, Yunsung Lee +5
Text classification in education, usually called auto-tagging, is the automated process of assigning relevant tags to educational content, such as questions and textbooks. However,…
Evaluation of Question Generation Needs More References
Shinhyeok Oh, Hyojun Go, Hyeongdon Moon +4
Question generation (QG) is the task of generating a valid and fluent question based on a given context and the target answer. According to various purposes, even given the same co…