3 papers
cs.IR2025
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…
cs.CL2025
LLM-guided Plan and Retrieval: A Strategic Alignment for Interpretable User Satisfaction Estimation in Dialogue
Sangyeop Kim, Sohhyung Park, Jaewon Jung +2
Understanding user satisfaction with conversational systems, known as User Satisfaction Estimation (USE), is essential for assessing dialogue quality and enhancing user experiences…
cs.CL2024
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…