7 citations · 7 across the 3 of their papers we have counts for
3 papers
cs.CV2024
Mitigating Adversarial Attacks in LLMs through Defensive Suffix Generation
Minkyoung Kim, Yunha Kim, Hyeram Seo +9
Large language models (LLMs) have exhibited outstanding performance in natural language processing tasks. However, these models remain susceptible to adversarial attacks in which s…
cs.CL2024★ 7 cited
Enhancing Clinical Efficiency through LLM: Discharge Note Generation for Cardiac Patients
HyoJe Jung, Yunha Kim, Heejung Choi +10
Medical documentation, including discharge notes, is crucial for ensuring patient care quality, continuity, and effective medical communication. However, the manual creation of the…
cs.CV2024
InMD-X: Large Language Models for Internal Medicine Doctors
Hansle Gwon, Imjin Ahn, Hyoje Jung +3
In this paper, we introduce InMD-X, a collection of multiple large language models specifically designed to cater to the unique characteristics and demands of Internal Medicine Doc…