1 citations · 1 across the 4 of their papers we have counts for
5 papers
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…
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…
Vivifying LIME: Visual Interactive Testbed for LIME Analysis
Jeongmin Rhee, Changhee Lee, DongHwa Shin +1
Explainable Artificial Intelligence (XAI) has gained importance in interpreting model predictions. Among leading techniques for XAI, Local Interpretable Model-agnostic Explanations…
MedOrchestra: A Hybrid Cloud-Local LLM Approach for Clinical Data Interpretation
Sihyeon Lee, Hyunjoo Song, Jong-chan Lee +6
Deploying large language models (LLMs) in clinical settings faces critical trade-offs: cloud LLMs, with their extensive parameters and superior performance, pose risks to sensitive…
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,…