6 papers
Bridging the Missing-Modality Gap: Improving Text-Only Calibration of Vision Language Models
Mingyeong Kim, Jungwon Choi, Chaeyun Jang +1
Vision-language models (VLMs) are often deployed on text-only inputs, although they are trained with images. We find that removing the vision modality causes large drops in accurac…
ForestPersons: A Large-Scale Dataset for Under-Canopy Missing Person Detection
Deokyun Kim, Jeongjun Lee, Jungwon Choi +6
Detecting missing persons in forest environments remains a challenge, as dense canopy cover often conceals individuals from detection in top-down or oblique aerial imagery typicall…
Joint-Embedding Masked Autoencoder for Self-supervised Learning of Dynamic Functional Connectivity from the Human Brain
Jungwon Choi, Hyungi Lee, Byung-Hoon Kim +1
Graph Neural Networks (GNNs) have shown promise in learning dynamic functional connectivity for distinguishing phenotypes from human brain networks. However, obtaining extensive la…
Stochastic Optimal Control for Diffusion Bridges in Function Spaces
Byoungwoo Park, Jungwon Choi, Sungbin Lim +1
Recent advancements in diffusion models and diffusion bridges primarily focus on finite-dimensional spaces, yet many real-world problems necessitate operations in infinite-dimensio…
A Foundational Brain Dynamics Model via Stochastic Optimal Control
Joonhyeong Park, Byoungwoo Park, Chang-Bae Bang +4
We introduce a foundational model for brain dynamics that utilizes stochastic optimal control (SOC) and amortized inference. Our method features a continuous-discrete state space m…
Model Fusion through Bayesian Optimization in Language Model Fine-Tuning
Chaeyun Jang, Hyungi Lee, Jungtaek Kim +1
Fine-tuning pre-trained models for downstream tasks is a widely adopted technique known for its adaptability and reliability across various domains. Despite its conceptual simplici…