Hyeonseok Moon
Korea University. NLP&AI Lab.
 Education
-  2024.02. - 2026.02(expected) Ph.D candidate in Computer Science 
at Korea University, South Korea -  2015.03. - 2021.02. B.A Degree of Science in Mathematics 
at Korea University, South Korea -  2015.03. - 2021.02. B.A Degree of Science in Artificial Intelligence 
at Korea University, South Korea 
Research Interest
- Language Resource and Evaluation
 - Large Language Model
 - Model Evaluation
 - Data Management and Engineering
 - Language Generation
 
selected publications
-  
 Metric Calculating Benchmark: Complicate Instruction Following Benchmark for Large Language ModelsIn The 2025 Conference on Empirical Methods in Natural Language Processing, 2025 -  
 LimaCost: Data Valuation for Instruction Tuning of Large Language ModelsIn Findings of the Association for Computational Linguistics: EMNLP 2025, 2025 -  
 The Impact of Negated Text on Hallucination with Large Language ModelsIn The 2025 Conference on Empirical Methods in Natural Language Processing, 2025 -  
 Call for Rigor in Reporting Quality of Instruction Tuning DataIn Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics, Jul 2025 -  
 Cross-Lingual Optimization for Language Transfer in Large Language ModelsIn Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics, Jul 2025 -  
 Semantic Aware Linear Transfer by Recycling Pre-trained Language Models for Cross-lingual TransferIn Findings of the Association for Computational Linguistics: ACL 2025, Jul 2025 -  
 FLEX: A Benchmark for Evaluating Robustness of Fairness in Large Language ModelsIn Findings of the Association for Computational Linguistics: NAACL 2025, Apr 2025 -  
 MIRAGE: A Metric-Intensive Benchmark for Retrieval-Augmented Generation EvaluationIn Findings of the Association for Computational Linguistics: NAACL 2025, Apr 2025 -  
 Find the Intention of Instruction: Comprehensive Evaluation of Instruction Understanding for Large Language ModelsIn Findings of the Association for Computational Linguistics: NAACL 2025, Apr 2025 -  
 Generative Interpretation: Toward Human-Like Evaluation for Educational Question-Answer Pair GenerationIn Findings of the Association for Computational Linguistics: EACL 2024, Mar 2024 -  
 CHEF in the Language Kitchen: A Generative Data Augmentation Leveraging Korean Morpheme IngredientsIn The 2023 Conference on Empirical Methods in Natural Language Processing, Mar 2023 -  
 Improving formality-sensitive machine translation using data-centric approaches and prompt engineeringIn Proceedings of the 20th International Conference on Spoken Language Translation (IWSLT 2023), Mar 2023 -  
 Doubts on the reliability of parallel corpus filteringExpert Systems with Applications, Jul 2023