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cs.CL2025

Everyday Physics in Korean Contexts: A Culturally Grounded Physical Reasoning Benchmark

Jihae Jeong, DaeYeop Lee, DongGeon Lee +1

Existing physical commonsense reasoning benchmarks predominantly focus on Western contexts, overlooking cultural variations in physical problem-solving. To address this gap, we int…

cs.CL2025

Are Vision-Language Models Safe in the Wild? A Meme-Based Benchmark Study

DongGeon Lee, Joonwon Jang, Jihae Jeong +1

Rapid deployment of vision-language models (VLMs) magnifies safety risks, yet most evaluations rely on artificial images. This study asks: How safe are current VLMs when confronted…

cs.CL2025

Typed-RAG: Type-Aware Decomposition of Non-Factoid Questions for Retrieval-Augmented Generation

DongGeon Lee, Ahjeong Park, Hyeri Lee +2

Addressing non-factoid question answering (NFQA) remains challenging due to its open-ended nature, diverse user intents, and need for multi-aspect reasoning. These characteristics…

cs.CL2025

REFIND at SemEval-2025 Task 3: Retrieval-Augmented Factuality Hallucination Detection in Large Language Models

DongGeon Lee, Hwanjo Yu

Hallucinations in large language model (LLM) outputs severely limit their reliability in knowledge-intensive tasks such as question answering. To address this challenge, we introdu…

cs.CL2025

Theme-Explanation Structure for Table Summarization using Large Language Models: A Case Study on Korean Tabular Data

TaeYoon Kwack, Jisoo Kim, Ki Yong Jung +2

Tables are a primary medium for conveying critical information in administrative domains, yet their complexity hinders utilization by Large Language Models (LLMs). This paper intro…