6 papers
STAR: Detecting Inference-time Backdoors in LLM Reasoning via State-Transition Amplification Ratio
Seong-Gyu Park, Sohee Park, Jisu Lee +2
Recent LLMs increasingly integrate reasoning mechanisms like Chain-of-Thought (CoT). However, this explicit reasoning exposes a new attack surface for inference-time backdoors, whi…
Self-HarmLLM: Can Large Language Model Harm Itself?
Heehwan Kim, Sungjune Park, Daeseon Choi
Large Language Models (LLMs) are generally equipped with guardrails to block the generation of harmful responses. However, existing defenses always assume that an external attacker…
IPG: Incremental Patch Generation for Generalized Adversarial Patch Training
Wonho Lee, Hyunsik Na, Jisu Lee +1
The advent of adversarial patches poses a significant challenge to the robustness of AI models, particularly in the domain of computer vision tasks such as object detection. In con…
Judgment-of-Thought Prompting: A Courtroom-Inspired Framework for Binary Logical Reasoning with Large Language Models
Sungjune Park, Heehwan Kim, Haehyun Cho +1
This paper proposes a novel prompting approach, Judgment of Thought (JoT), specifically tailored for binary logical reasoning tasks. Despite advances in prompt engineering, existin…
RoVo: Robust Voice Protection Against Unauthorized Speech Synthesis with Embedding-Level Perturbations
Seungmin Kim, Sohee Park, Donghyun Kim +2
With the advancement of AI-based speech synthesis technologies such as Deep Voice, there is an increasing risk of voice spoofing attacks, including voice phishing and fake news, th…
Robustness Analysis against Adversarial Patch Attacks in Fully Unmanned Stores
Hyunsik Na, Wonho Lee, Seungdeok Roh +2
The advent of convenient and efficient fully unmanned stores equipped with artificial intelligence-based automated checkout systems marks a new era in retail. However, these system…