collaborators

6 papers

cs.AI2026

Citation-Closure Retrieval and Per-Rule Attribution for Real-World Regulatory Compliance Question Answering

Yeong-Joon Ju, Seong-Whan Lee

Deploying Large Language Models (LLMs) for regulatory compliance demands rigorous traceability via comprehensive citations across multi-tiered authority structures. Unlike traditio…

cs.LG2026

From Generator to Embedder: Harnessing Innate Abilities of Multimodal LLMs via Building Zero-Shot Discriminative Embedding Model

Yeong-Joon Ju, Seong-Whan Lee

Adapting generative Multimodal Large Language Models (MLLMs) into universal embedding models typically demands resource-intensive contrastive pre-training, while traditional hard n…

cs.CL2025

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…

cs.CL2025

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…

cs.CL2025

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…

cs.CV2025

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…