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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.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…