16 citations · 23 across the 19 of their papers we have counts for
20 papers · 1 filter
Living Dashboards: Automatically Self-Updating Visualization Dashboards
Mingyu An, Heyon Jeon, Sungbok Shin +4
Visualization dashboards are widely used interactive tools, but a disconnect exists between the dynamic data they display and their static structure. End-users cannot modify the da…
Penquiry: A Pen-based Interactive In-situ Q&A System Leveraging LLMs
Jeongmin Rhee, Changhee Lee, Hyunwoo Kim +4
Pen-based digital devices remain a preferred medium for active, cognitively engaging study. Concurrently, Large Language Models (LLMs) have become indispensable for self-directed l…
ggaction: A Grammar of Graphical Actions
Hyeon Jeon, Jinwook Seo
A chart may be declarative; authoring it is not. Visualization grammars often describe charts as finished specifications, whereas people construct them through a sequence of author…
TailVis: Expressive Chart Refinement Preserving Data-Binding Integrity
Yumin Song, Seokhyeon Park, Soohyun Lee +4
Creating static visualizations for presentations and publications requires granular refinements of visual details, even for simple charts. Existing data-driven visualization tools…
Physical Containers as Framing Conditions for Visualization in Augmented Reality
Jiyeon Bae, Mingyu An, Jeongin Park +3
Exploratory data analysis (EDA) is often hindered by cold-start friction; when users lack specific analytic goals, they struggle to configure complex visualization parameters. Whil…
A Multi-Level Visual Analytics Approach to Artist-Era Alignment in Popular Music
Jiyeon Bae, Jinwook Seo
Existing computational studies of popular music primarily model aggregate trends or predict chart performance, offering limited support for interpreting artist-level alignment agai…
Seeing Graphs Like Humans: Benchmarking Computational Measures and MLLMs for Similarity Assessment
Seokweon Jung, Jeongmin Rhee, Seoyoung Doh +3
Comparing graphs to identify similarities is a fundamental task in visual analytics of graph data. To support this, visual analytics systems frequently employ quantitative computat…
InFerActive: Interactive Tree-Based Exploration of LLM Sampling for Safety Evaluation
Junhyeong Hwangbo, Soohyun Lee, Hyeon Jeon +4
Even LLMs that appear safe during evaluation can still produce harmful responses in deployment. Because stochastic sampling yields different responses to the same prompt, low-proba…
Understanding Bias in Perceiving Dimensionality Reduction Projections
Seoyoung Doh, Hyeon Jeon, Sungbok Shin +3
Selecting the dimensionality reduction technique that faithfully represents the structure is essential for reliable visual communication and analytics. In reality, however, practit…
Dataset-Adaptive Dimensionality Reduction
Hyeon Jeon, Jeongin Park, Soohyun Lee +3
Selecting the appropriate dimensionality reduction (DR) technique and determining its optimal hyperparameter settings that maximize the accuracy of the output projections typically…
Stop Misusing t-SNE and UMAP for Visual Analytics
Hyeon Jeon, Jeongin Park, Sungbok Shin +1
Misuses of t-SNE and UMAP in visual analytics have become increasingly common. For example, although t-SNE and UMAP projections often do not faithfully reflect the original distanc…
Can VLMs Assess Similarity Between Graph Visualizations?
Seokweon Jung, Hyeon Jeon, Jeongmin Rhee +1
Graph visualizations have been studied for tasks such as clustering and temporal analysis, but how these visual similarities relate to established graph similarity measures remains…
Unveiling High-dimensional Backstage: A Survey for Reliable Visual Analytics with Dimensionality Reduction
Hyeon Jeon, Hyunwook Lee, Yun-Hsin Kuo +6
Dimensionality reduction (DR) techniques are essential for visually analyzing high-dimensional data. However, visual analytics using DR often face unreliability, stemming from fact…
Beyond Tools: Understanding How Heavy Users Integrate LLMs into Everyday Tasks and Decision-Making
Eunhye Kim, Kiroong Choe, Minju Yoo +2
Large language models (LLMs) are increasingly used for both everyday and specialized tasks. While HCI research focuses on domain-specific applications, little is known about how he…
Efficiently Crowdsourcing Visual Importance with Punch-Hole Annotation
Minsuk Chang, Soohyun Lee, Aeri Cho +4
We introduce a novel crowdsourcing method for identifying important areas in graphical images through punch-hole labeling. Traditional methods, such as gaze trackers and mouse-base…
PhenoFlow: A Human-LLM Driven Visual Analytics System for Exploring Large and Complex Stroke Datasets
Jaeyoung Kim, Sihyeon Lee, Hyeon Jeon +4
Acute stroke demands prompt diagnosis and treatment to achieve optimal patient outcomes. However, the intricate and irregular nature of clinical data associated with acute stroke,…
Offsetting Perceptual Bias in Visual Clustering: The Role of Point Size Adjustment in Variable Display Sizes
Taehyun Yang, Hyeon Jeon, Jinwook Seo
Scatterplots are frequently shared across different displays in collaborative and communicative visual analytics. However, variations in displays diversify scatterplot sizes. Such…
Fields, Bridges, and Foundations: How Researchers Browse Citation Network Visualizations
Kiroong Choe, Eunhye Kim, Sangwon Park +1
Visualizing citation relations with network structures is widely used, but the visual complexity can make it challenging for individual researchers trying to navigate them. We coll…
Combinational Nonuniform Timeslicing of Dynamic Networks
Seokweon Jung, DongHwa Shin, Hyeon Jeon +1
Dynamic networks represent the complex and evolving interrelationships between real-world entities. Given the scale and variability of these networks, finding an optimal slicing in…
CloChat: Understanding How People Customize, Interact, and Experience Personas in Large Language Models
Juhye Ha, Hyeon Jeon, DaEun Han +2
Large language models (LLMs) have facilitated significant strides in generating conversational agents, enabling seamless, contextually relevant dialogues across diverse topics. How…