9 citations · 19 across the 13 of their papers we have counts for
13 papers
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…
Revisiting Channel Effectiveness: A Multi-Dimensional Evaluation with Primitive Visual Stimuli
Soohyun Lee, Seokhyeon Park, Minsuk Chang +1
Established channel effectiveness rankings primarily assess magnitude estimation accuracy in complete chart contexts, often neglecting other perceptual tasks such as discriminabili…
Disentangling Visual and Factual Correctness in LVLMs' Visualization Literacy
Soohyun Lee, Jaeyoung Kim, Seokhyeon Park +5
Large Vision-Language Models (LVLMs) show strong visualization interpretation, yet it is unclear whether their responses reflect genuine reasoning over visual evidence or factual p…
HookLens: Visual Analytics for Understanding React Hooks Structures
Suyeon Hwang, Minkyu Kweon, Jeongmin Rhee +5
Maintaining and refactoring React web applications is challenging, as React code often becomes complex due to its core API called Hooks. For example, Hooks often lead developers to…
Bridging Gulfs in UI Generation through Semantic Guidance
Seokhyeon Park, Soohyun Lee, Eugene Choi +4
While generative AI enables high-fidelity UI generation from text prompts, users struggle to articulate design intent and evaluate or refine results-creating gulfs of execution and…
GhostUI: Unveiling Hidden Interactions in Mobile UI
Minkyu Kweon, Seokhyeon Park, Soohyun Lee +3
Modern mobile applications rely on hidden interactions--gestures without visual cues like long presses and swipes--to provide functionality without cluttering interfaces. While exp…
Measuring the Validity of Clustering Validation Datasets
Hyeon Jeon, Michaël Aupetit, DongHwa Shin +3
Clustering techniques are often validated using benchmark datasets where class labels are used as ground-truth clusters. However, depending on the datasets, class labels may not al…
Leveraging Multimodal LLM for Inspirational User Interface Search
Seokhyeon Park, Yumin Song, Soohyun Lee +2
Inspirational search, the process of exploring designs to inform and inspire new creative work, is pivotal in mobile user interface (UI) design. However, exploring the vast space o…
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…
Assessing Graphical Perception of Image Embedding Models using Channel Effectiveness
Soohyun Lee, Minsuk Chang, Seokhyeon Park +1
Recent advancements in vision models have greatly improved their ability to handle complex chart understanding tasks, like chart captioning and question answering. However, it rema…
Extracting Human Attention through Crowdsourced Patch Labeling
Minsuk Chang, Seokhyeon Park, Hyeon Jeon +3
In image classification, a significant problem arises from bias in the datasets. When it contains only specific types of images, the classifier begins to rely on shortcuts - simpli…
Computational Approaches for App-to-App Retrieval and Design Consistency Check
Seokhyeon Park, Wonjae Kim, Young-Ho Kim +1
Extracting semantic representations from mobile user interfaces (UI) and using the representations for designers' decision-making processes have shown the potential to be effective…
Sanity Check for External Clustering Validation Benchmarks using Internal Validation Measures
Hyeon Jeon, Michael Aupetit, DongHwa Shin +3
We address the lack of reliability in benchmarking clustering techniques based on labeled datasets. A standard scheme in external clustering validation is to use class labels as gr…