3 papers
cs.CV2026
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…
cs.CL2025
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…
cs.HC2024
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,…