2 citations · 2 across the 3 of their papers we have counts for
4 papers
Multi-stage Prompt Refinement for Mitigating Hallucinations in Large Language Models
Jung-Woo Shim, Yeong-Joon Ju, Ji-Hoon Park +1
Recent advancements in large language models (LLMs) have shown strong performance in natural language understanding and generation tasks. However, LLMs continue to encounter challe…
CPR: Mitigating Large Language Model Hallucinations with Curative Prompt Refinement
Jung-Woo Shim, Yeong-Joon Ju, Ji-Hoon Park +1
Recent advancements in large language models (LLMs) highlight their fluency in generating responses to diverse prompts. However, these models sometimes generate plausible yet incor…
XLQA: A Benchmark for Locale-Aware Multilingual Open-Domain Question Answering
Keon-Woo Roh, Yeong-Joon Ju, Seong-Whan Lee
Large Language Models (LLMs) have shown significant progress in Open-domain question answering (ODQA), yet most evaluations focus on English and assume locale-invariant answers acr…
MIRe: Enhancing Multimodal Queries Representation via Fusion-Free Modality Interaction for Multimodal Retrieval
Yeong-Joon Ju, Ho-Joong Kim, Seong-Whan Lee
Recent multimodal retrieval methods have endowed text-based retrievers with multimodal capabilities by utilizing pre-training strategies for visual-text alignment. They often direc…