collaborators

7 papers

cs.CL2026

IHDec: Divergence-Steered Contrastive Decoding for Securing Multi-Turn Instruction Hierarchies

Nicole Geumheon Liu, Haeun Jang, Yonghyun Jun +1

Large Language Models (LLMs) often fail to maintain instruction hierarchies (IH) when processing multi-source inputs with varying role-level priorities, paradoxically adhering to l…

cs.CL2026

Code-Switching Reveals Language Anchoring in Multilingual LLMs

Jeonghyun Park, Seunghyun Yoon, Yonghyun Jun +1

Multilingual Large Language Models (MLLMs) are increasingly expected to handle Code-Switched (CS) inputs, yet mixing languages frequently degrades performance relative to source- o…

cs.CL2026

Identifying and Mitigating Bottlenecks in Role-Playing Agents: A Systematic Study of Disentangling Character Profile Axes

Yonghyun Jun, Junhyuk Choi, Jeonghyun Park +3

While Large Language Model (LLM) role-playing agents have advanced rapidly, it remains unclear which profile elements genuinely drive role-playing quality. To bridge this gap, we i…

cs.CL2026

ChatInject: Abusing Chat Templates for Prompt Injection in LLM Agents

Hwan Chang, Yonghyun Jun, Hwanhee Lee

The growing deployment of large language model (LLM) based agents that interact with external environments has created new attack surfaces for adversarial manipulation. One major t…

cs.CL2025

Keep Security! Benchmarking Security Policy Preservation in Large Language Model Contexts Against Indirect Attacks in Question Answering

Hwan Chang, Yumin Kim, Yonghyun Jun +1

As Large Language Models (LLMs) are increasingly deployed in sensitive domains such as enterprise and government, ensuring that they adhere to user-defined security policies within…

cs.CL2025

Dynamic Order Template Prediction for Generative Aspect-Based Sentiment Analysis

Yonghyun Jun, Hwanhee Lee

Aspect-based sentiment analysis (ABSA) assesses sentiments towards specific aspects within texts, resulting in detailed sentiment tuples. Previous ABSA models often use static temp…