2 citations · 2 across the 5 of their papers we have counts for
5 papers · 1 filter
Anonpsy: A Graph-Based Framework for Structure-Preserving De-identification of Psychiatric Narratives
Kyung Ho Lim, Byung-Hoon Kim
Psychiatric narratives encode patient identity not only through explicit identifiers but also through idiosyncratic life events embedded in their clinical structure. Existing de-id…
AutoMedic: An Automated Evaluation Framework for Clinical Conversational Agents with Medical Dataset Grounding
Gyutaek Oh, Sangjoon Park, Byung-Hoon Kim
Evaluating large language models (LLMs) has recently emerged as a critical issue for safe and trustworthy application of LLMs in the medical domain. Although a variety of static me…
Rethinking Test-Time Scaling for Medical AI: Model and Task-Aware Strategies for LLMs and VLMs
Gyutaek Oh, Seoyeon Kim, Sangjoon Park +1
Test-time scaling has recently emerged as a promising approach for enhancing the reasoning capabilities of large language models or vision-language models during inference. Althoug…
Susceptibility of Large Language Models to User-Driven Factors in Medical Queries
Kyung Ho Lim, Ujin Kang, Xiang Li +4
Large language models (LLMs) are increasingly used in healthcare, but their reliability is heavily influenced by user-driven factors such as question phrasing and the completeness…
PSYCHE: A Multi-faceted Patient Simulation Framework for Evaluation of Psychiatric Assessment Conversational Agents
Jingoo Lee, Kyungho Lim, Young-Chul Jung +1
Recent advances in large language models (LLMs) have accelerated the development of conversational agents capable of generating human-like responses. Since psychiatric assessments…