7 papers
How Do LLMs See Charts? A Comparative Study on High-Level Visualization Comprehension in Humans and LLMs
Hyotaek Jeon, Hyunwook Lee, Minjeong Shin +6
Designers often create visualizations to achieve specific high-level analytical or communication goals. These goals require people to extract complex and interconnected data patter…
VEHME: A Vision-Language Model For Evaluating Handwritten Mathematics Expressions
Thu Phuong Nguyen, Duc M. Nguyen, Hyotaek Jeon +4
Automatically assessing handwritten mathematical solutions is an important problem in educational technology with practical applications, but it remains a significant challenge due…
From Patterns to Predictions: A Shapelet-Based Framework for Directional Forecasting in Noisy Financial Markets
Juwon Kim, Hyunwook Lee, Hyotaek Jeon +2
Directional forecasting in financial markets requires both accuracy and interpretability. Before the advent of deep learning, interpretable approaches based on human-defined patter…
ST-LINK: Spatially-Aware Large Language Models for Spatio-Temporal Forecasting
Hyotaek Jeon, Hyunwook Lee, Juwon Kim +1
Traffic forecasting represents a crucial problem within intelligent transportation systems. In recent research, Large Language Models (LLMs) have emerged as a promising method, but…
Navigating High-Dimensional Backstage: A Guide for Exploring Literature for the Reliable Use of Dimensionality Reduction
Hyeon Jeon, Hyunwook Lee, Yun-Hsin Kuo +6
Visual analytics using dimensionality reduction (DR) can easily be unreliable for various reasons, e.g., inherent distortions in representing the original data. The literature has…
Beyond the Mirror: Personal Analytics through Visual Juxtaposition with Other People's Data
Sungbok Shin, Sunghyo Chung, Hyeon Jeon +6
An individual's data can reveal facets of behavior and identity, but its interpretation is context dependent. We can easily identify various self-tracking applications that help pe…