33 citations · 33 across the 6 of their papers we have counts for
6 papers
EXAONE 4.5 Technical Report
Eunbi Choi, Kibong Choi, Sehyun Chun +55
This technical report introduces EXAONE 4.5, the first open-weight vision language model released by LG AI Research. EXAONE 4.5 is architected by integrating a dedicated visual enc…
PRISP: Privacy-Safe Few-Shot Personalization via Lightweight Adaptation
Junho Park, Dohoon Kim, Taesup Moon
Large language model (LLM) personalization aims to adapt general-purpose models to individual users. Most existing methods, however, are developed under data-rich and resource-abun…
DoMIX: An Efficient Framework for Exploiting Domain Knowledge in Fine-Tuning
Dohoon Kim, Donghun Kang, Taesup Moon
Domain-Adaptive Pre-training (DAP) has recently gained attention for its effectiveness in fine-tuning pre-trained models. Building on this, continual DAP has been explored to devel…
MADCluster: Model-agnostic Anomaly Detection with Self-supervised Clustering Network
Sangyong Lee, Subo Hwang, Dohoon Kim
In this paper, we propose MADCluster, a novel model-agnostic anomaly detection framework utilizing self-supervised clustering. MADCluster is applicable to various deep learning arc…
MAFA: Managing False Negatives for Vision-Language Pre-training
Jaeseok Byun, Dohoon Kim, Taesup Moon
We consider a critical issue of false negatives in Vision-Language Pre-training (VLP), a challenge that arises from the inherent many-to-many correspondence of image-text pairs in…
Semi-orthogonal Embedding for Efficient Unsupervised Anomaly Segmentation
Jin-Hwa Kim, Do-Hyeong Kim, Saehoon Yi +1
We present the efficiency of semi-orthogonal embedding for unsupervised anomaly segmentation. The multi-scale features from pre-trained CNNs are recently used for the localized Mah…