6 papers
Natural Language Declarative Prompting (NLD-P): A Modular Governance Method for Prompt Design Under Model Drift
Hyunwoo Kim, Hanau Yi, Jaehee Bae +1
The rapid evolution of large language models (LLMs) has transformed prompt engineering from a localized craft into a systems-level governance challenge. As models scale and update…
MultiLexNorm++: A Unified Benchmark and a Generative Model for Lexical Normalization for Asian Languages
Weerayut Buaphet, Thanh-Nhi Nguyen, Risa Kondo +8
Social media data has been of interest to Natural Language Processing (NLP) practitioners for over a decade, because of its richness in information, but also challenges for automat…
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…
Selective Demonstration Retrieval for Improved Implicit Hate Speech Detection
Yumin Kim, Hwanhee Lee
Hate speech detection is a crucial area of research in natural language processing, essential for ensuring online community safety. However, detecting implicit hate speech, where h…
Personality Editing for Language Models through Adjusting Self-Referential Queries
Seojin Hwang, Yumin Kim, Byeongjeong Kim +2
Large Language Models (LLMs) are integral to applications such as conversational agents and content creation, where precise control over a model's personality is essential for main…
KoCoSa: Korean Context-aware Sarcasm Detection Dataset
Yumin Kim, Heejae Suh, Mingi Kim +2
Sarcasm is a way of verbal irony where someone says the opposite of what they mean, often to ridicule a person, situation, or idea. It is often difficult to detect sarcasm in the d…