3 papers
cs.IR2025
C: Capturing Consensus with Contrastive Learning in Group Recommendation
Soyoung Kim, Dongjun Lee, Jaekwang Kim
Group recommendation aims to recommend tailored items to groups of users, where the key challenge is modeling a consensus that reflects member preferences. Although several existin…
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…