3 papers
cs.CL2025
QUPID: Quantified Understanding for Enhanced Performance, Insights, and Decisions in Korean Search Engines
Ohjoon Kwon, Changsu Lee, Jihye Back +3
Large language models (LLMs) have been widely used for relevance assessment in information retrieval. However, our study demonstrates that combining two distinct small language mod…
cs.IR2025
Taxonomy and Analysis of Sensitive User Queries in Generative AI Search
Hwiyeol Jo, Taiwoo Park, Hyunwoo Lee +10
Although there has been a growing interest among industries in integrating generative LLMs into their services, limited experience and scarcity of resources act as a barrier in lau…
cs.CL2024
Zero-Shot Multi-Hop Question Answering via Monte-Carlo Tree Search with Large Language Models
Seongmin Lee, Jaewook Shin, Youngjin Ahn +3
Recent advances in large language models (LLMs) have significantly impacted the domain of multi-hop question answering (MHQA), where systems are required to aggregate information a…