Demo Data from VLDB 2026 / reviewers in the wild / expert
Kyu Won Kim
dblp:75/10566
· DBLP profile ↗
2ranked-venue papers
0as first author
2since 2021 · last 2024
0009-0008-6334-2581ORCID · corroborated
Domains — the database's venue-derived domains; a paper can count in several
Human-computer interaction and ubiquitous computing · 2 · 2 since 2021
Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.
| Human-computer interaction and pervasive computing
2 papers |
User interface design and tools · 86% Human-AI interaction · 14% | |
| Artificial intelligence
1 paper |
Generative modeling · 100% | |
| Computer graphics and multimedia
1 paper |
Geometric modeling and processing · 100% |
Topics — the 5 heaviest of 5, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Machine learning › Generative modeling › diffusion model
text-to-image generation |
0.8 | 1 | 2024 | Prompting for Discovery: Flexible Sense-Making for AI Art-Making with Dreamsheets · CHI 2024 |
User interface design and tools
creativity support tools |
0.8 | 1 | 2024 | Prompting for Discovery: Flexible Sense-Making for AI Art-Making with Dreamsheets · CHI 2024 |
Geometric modeling and processing › shape representation › vector graphics
vector graphics editing |
0.7 | 1 | 2023 | Interactive Flexible Style Transfer for Vector Graphics · UIST 2023 |
User interface design and tools
design tools |
0.7 | 1 | 2023 | Interactive Flexible Style Transfer for Vector Graphics · UIST 2023 |
Human-AI interaction › AI-assisted creativity
LLM-assisted design |
0.2 | 1 | 2024 | Prompting for Discovery: Flexible Sense-Making for AI Art-Making with Dreamsheets · CHI 2024 |
Methods — techniques the papers use, named apart from their topics
longitudinal study · 1.5design probe · 1.5style transfer · 1.3
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2024 | Prompting for Discovery: Flexible Sense-Making for AI Art-Making with DreamsheetsabstractDesign space exploration (DSE) for Text-to-Image (TTI) models entails navigating a vast, opaque space of possible image outputs, through a commensurately vast input space of hyperparameters and prompt text. Perceptually small movements in prompt-space can surface unexpectedly disparate images. How can interfaces support end-users in reliably steering prompt-space explorations towards interesting results? Our design probe, DreamSheets, supports user-composed exploration strategies with LLM-assisted prompt construction and large-scale simultaneous display of generated results, hosted in a spreadsheet interface. Two studies, a preliminary lab study and an extended two-week study where five expert artists developed custom TTI sheet-systems, reveal various strategies for targeted TTI design space exploration—such as using templated text generation to define and layer semantic “axes” for exploration. We identified patterns in exploratory structures across our participants’ sheet-systems: configurable exploration “units” that we distill into a UI mockup, and generalizable UI components to guide future interfaces. Shm Garanganao Almeda, J. D. Zamfirescu-Pereira, Kyu Won Kim, Pradeep Mani Rathnam, Björn Hartmann |
CHI | 3 |
| 2023 | Interactive Flexible Style Transfer for Vector GraphicsabstractVector graphics are an industry-standard way to represent and share visual designs. Designers frequently source and incorporate styles from existing designs into their work. Unfortunately, popular design tools are not well suited for this task. We present VST, Vector Style Transfer, a novel design tool for flexibly transferring visual styles between vector graphics. The core of VST lies in leveraging automation while respecting designers’ tastes and the subjectivity inherent to style transfer. In VST, designers tune a cross-design element correspondence and customize which style attributes to change. We report results from a user study in which designers used VST to control style transfer between several designs, including designs participants created with external tools beforehand. VST shows that enabling design correspondence tuning and customization is one way to support interactive, flexible style transfer. Jeremy Warner, Kyu Won Kim, Björn Hartmann |
UIST | 2 |