16 citations · 23 across the 19 of their papers we have counts for
8 papers · 1 filter
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…
Metric Design != Metric Behavior: Improving Metric Selection for the Unbiased Evaluation of Dimensionality Reduction
Jiyeon Bae, Hyeon Jeon, Jinwook Seo
Evaluating the accuracy of dimensionality reduction (DR) projections in preserving the structure of high-dimensional data is crucial for reliable visual analytics. Diverse evaluati…
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…