5 citations · 12 across the 19 of their papers we have counts for
6 papers · 1 filter
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…
Enhancement of text recognition for hanja handwritten documents of Ancient Korea
Joonmo Ahna, Taehong Jang, Quan Fengnyu +3
We implemented a high-performance optical character recognition model for classical handwritten documents using data augmentation with highly variable cropping within the document…
Reliable Decision Making via Calibration Oriented Retrieval Augmented Generation
Chaeyun Jang, Deukhwan Cho, Seanie Lee +2
Recently, Large Language Models (LLMs) have been increasingly used to support various decision-making tasks, assisting humans in making informed decisions. However, when LLMs confi…
Amortized Control of Continuous State Space Feynman-Kac Model for Irregular Time Series
Byoungwoo Park, Hyungi Lee, Juho Lee
Many real-world datasets, such as healthcare, climate, and economics, are often collected as irregular time series, which poses challenges for accurate modeling. In this paper, we…
Enhancing Transfer Learning with Flexible Nonparametric Posterior Sampling
Hyungi Lee, Giung Nam, Edwin Fong +1
Transfer learning has recently shown significant performance across various tasks involving deep neural networks. In these transfer learning scenarios, the prior distribution for d…
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…