4 papers
Upcycling Candidate Tokens of Large Language Models for Query Expansion
Jinseok Kim, Sukmin Cho, Soyeong Jeong +2
Query Expansion (QE) improves retrieval performance by enriching queries with related terms. Recently, Large Language Models (LLMs) have been used for QE, but existing methods face…
EXPERT: An Explainable Image Captioning Evaluation Metric with Structured Explanations
Hyunjong Kim, Sangyeop Kim, Jongheon Jeong +2
Recent advances in large language models and vision-language models have led to growing interest in explainable evaluation metrics for image captioning. However, these metrics gene…
What Really Matters in Many-Shot Attacks? An Empirical Study of Long-Context Vulnerabilities in LLMs
Sangyeop Kim, Yohan Lee, Yongwoo Song +1
We investigate long-context vulnerabilities in Large Language Models (LLMs) through Many-Shot Jailbreaking (MSJ). Our experiments utilize context length of up to 128K tokens. Throu…
Safe-Embed: Unveiling the Safety-Critical Knowledge of Sentence Encoders
Jinseok Kim, Jaewon Jung, Sangyeop Kim +2
Despite the impressive capabilities of Large Language Models (LLMs) in various tasks, their vulnerability to unsafe prompts remains a critical issue. These prompts can lead LLMs to…