3 papers
cs.CV2024
Debiasing Classifiers by Amplifying Bias with Latent Diffusion and Large Language Models
Donggeun Ko, Dongjun Lee, Namjun Park +2
Neural networks struggle with image classification when biases are learned and misleads correlations, affecting their generalization and performance. Previous methods require attri…
cs.CV2024
DiffInject: Revisiting Debias via Synthetic Data Generation using Diffusion-based Style Injection
Donggeun Ko, Sangwoo Jo, Dongjun Lee +2
Dataset bias is a significant challenge in machine learning, where specific attributes, such as texture or color of the images are unintentionally learned resulting in detrimental…
cs.IR2023
Hierarchical Contrastive Learning with Multiple Augmentation for Sequential Recommendation
Dongjun Lee, Donggeun Ko, Jaekwang Kim
Sequential recommendation addresses the issue of preference drift by predicting the next item based on the user's previous behaviors. Recently, a promising approach using contrasti…