1 citations · 2 across the 6 of their papers we have counts for
7 papers
Is Prompt Selection Necessary for Task-Free Online Continual Learning?
Seoyoung Park, Haemin Lee, Hankook Lee
Task-free online continual learning has recently emerged as a realistic paradigm for addressing continual learning in dynamic, real-world environments, where data arrive in a non-s…
Training-free Detection of AI-generated images via Cropping Robustness
Sungik Choi, Hankook Lee, Moontae Lee
AI-generated image detection has become crucial with the rapid advancement of vision-generative models. Instead of training detectors tailored to specific datasets, we study a trai…
Partial-Multivariate Model for Forecasting
Jaehoon Lee, Hankook Lee, Sungik Choi +2
When solving forecasting problems including multiple time-series features, existing approaches often fall into two extreme categories, depending on whether to utilize inter-feature…
Diffusion based Semantic Outlier Generation via Nuisance Awareness for Out-of-Distribution Detection
Suhee Yoon, Sanghyu Yoon, Ye Seul Sim +5
Out-of-distribution (OOD) detection, which determines whether a given sample is part of the in-distribution (ID), has recently shown promising results through training with synthet…
Learning Equi-angular Representations for Online Continual Learning
Minhyuk Seo, Hyunseo Koh, Wonje Jeung +7
Online continual learning suffers from an underfitted solution due to insufficient training for prompt model update (e.g., single-epoch training). To address the challenge, we prop…
Projection Regret: Reducing Background Bias for Novelty Detection via Diffusion Models
Sungik Choi, Hankook Lee, Honglak Lee +1
Novelty detection is a fundamental task of machine learning which aims to detect abnormal ( out-of-distribution (OOD)) samples. Since diffusion models have recently…
Curve Your Attention: Mixed-Curvature Transformers for Graph Representation Learning
Sungjun Cho, Seunghyuk Cho, Sungwoo Park +3
Real-world graphs naturally exhibit hierarchical or cyclical structures that are unfit for the typical Euclidean space. While there exist graph neural networks that leverage hyperb…