Towards Precise Localization of Critical Errors in Machine Translation

KoCommonGEN v2: A Benchmark for Navigating Korean Commonsense Reasoning Challenges in Large Language Models

Length-aware Byte Pair Encoding for Mitigating Over-segmentation in Korean Machine Translation

Open Ko-LLM Leaderboard: Evaluating Large Language Models in Korean with Ko-H5 Benchmark

Exploring Inherent Biases in LLMs within Korean Social Context: A Comparative Analysis of ChatGPT and GPT-4

Explainable CED: A Dataset for Explainable Critical Error Detection in Machine Translation

KNOTICED: A Dataset for Critical Error Detection in English-Korean Machine Translation

Leveraging Pre-existing Resources for Data-Efficient Counter-Narrative Generation in Korean

Ask, Assess, and Refine: Rectifying Factual Consistency and Hallucination in LLMs with Metric-Guided Feedback Learning

Generative Interpretation: Toward Human-Like Evaluation for Educational Question-Answer Pair Generation