2 citations · 2 across the 4 of their papers we have counts for
6 papers
Strong Helps Weak: Directional Cross-Modal Alignment Transfer in Multi-modal LLMs
Hoigi Seo, Byung Hyun Lee, Minjun Kim +3
Multi-modal large language models (MLLMs) achieve strong modality understanding by pairing a large language model (LLM) with an encoder for a target modality such as vision, video,…
On Epistemic Uncertainty of Visual Tokens for Object Hallucinations in Large Vision-Language Models
Hoigi Seo, Dong Un Kang, Hyunjin Cho +2
Large vision-language models (LVLMs), which integrate a vision encoder (VE) with a large language model, have achieved remarkable success across various tasks. However, there are s…
Concept Pinpoint Eraser for Text-to-image Diffusion Models via Residual Attention Gate
Byung Hyun Lee, Sungjin Lim, Seunggyu Lee +2
Remarkable progress in text-to-image diffusion models has brought a major concern about potentially generating images on inappropriate or trademarked concepts. Concept erasing has…
Doubly Perturbed Task Free Continual Learning
Byung Hyun Lee, Min-hwan Oh, Se Young Chun
Task Free online continual learning (TF-CL) is a challenging problem where the model incrementally learns tasks without explicit task information. Although training with entire dat…
Online Continual Learning on Hierarchical Label Expansion
Byung Hyun Lee, Okchul Jung, Jonghyun Choi +1
Continual learning (CL) enables models to adapt to new tasks and environments without forgetting previously learned knowledge. While current CL setups have ignored the relationship…
Adaptive GLCM sampling for transformer-based COVID-19 detection on CT
Okchul Jung, Dong Un Kang, Gwanghyun Kim +1
The world has suffered from COVID-19 (SARS-CoV-2) for the last two years, causing much damage and change in people's daily lives. Thus, automated detection of COVID-19 utilizing de…