Hyeonseok Moon
Orcid: 0000-0002-0841-4262
According to our database1,
Hyeonseok Moon
authored at least 40 papers
between 2021 and 2024.
Collaborative distances:
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Bibliography
2024
Toward Practical Automatic Speech Recognition and Post-Processing: a Call for Explainable Error Benchmark Guideline.
CoRR, 2024
Exploiting Hanja-Based Resources in Processing Korean Historic Documents Written by Common Literati.
IEEE Access, 2024
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2024, 2024
Hyper-BTS Dataset: Scalability and Enhanced Analysis of Back TranScription (BTS) for ASR Post-Processing.
Proceedings of the Findings of the Association for Computational Linguistics: EACL 2024, 2024
Generative Interpretation: Toward Human-Like Evaluation for Educational Question-Answer Pair Generation.
Proceedings of the Findings of the Association for Computational Linguistics: EACL 2024, 2024
Leveraging Pre-existing Resources for Data-Efficient Counter-Narrative Generation in Korean.
Proceedings of the 2024 Joint International Conference on Computational Linguistics, 2024
Detecting Critical Errors Considering Cross-Cultural Factors in English-Korean Translation.
Proceedings of the 2024 Joint International Conference on Computational Linguistics, 2024
Length-aware Byte Pair Encoding for Mitigating Over-segmentation in Korean Machine Translation.
Proceedings of the Findings of the Association for Computational Linguistics, 2024
2023
Expert Syst. Appl., December, 2023
Data-Driven Approach for Formality-Sensitive Machine Translation: Language-Specific Handling and Synthetic Data Generation.
CoRR, 2023
Synthetic Alone: Exploring the Dark Side of Synthetic Data for Grammatical Error Correction.
CoRR, 2023
Self-Improving-Leaderboard(SIL): A Call for Real-World Centric Natural Language Processing Leaderboards.
CoRR, 2023
Uncovering the Risks and Drawbacks Associated With the Use of Synthetic Data for Grammatical Error Correction.
IEEE Access, 2023
Improving Formality-Sensitive Machine Translation Using Data-Centric Approaches and Prompt Engineering.
Proceedings of the 20th International Conference on Spoken Language Translation, 2023
Informative Evidence-guided Prompt-based Fine-tuning for English-Korean Critical Error Detection.
Proceedings of the 13th International Joint Conference on Natural Language Processing and the 3rd Conference of the Asia-Pacific Chapter of the Association for Computational Linguistics, 2023
CHEF in the Language Kitchen: A Generative Data Augmentation Leveraging Korean Morpheme Ingredients.
Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, 2023
Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, 2023
Post-hoc Utterance Refining Method by Entity Mining for Faithful Knowledge Grounded Conversations.
Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, 2023
Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics: System Demonstrations, 2023
Towards Diverse and Effective Question-Answer Pair Generation from Children Storybooks.
Proceedings of the Findings of the Association for Computational Linguistics: ACL 2023, 2023
2022
PU-GEN: Enhancing generative commonsense reasoning for language models with human-centered knowledge.
Knowl. Based Syst., 2022
IEEE Access, 2022
IEEE Access, 2022
Mimicking Infants' Bilingual Language Acquisition for Domain Specialized Neural Machine Translation.
IEEE Access, 2022
IEEE Access, 2022
K-NCT: Korean Neural Grammatical Error Correction Gold-Standard Test Set Using Novel Error Type Classification Criteria.
IEEE Access, 2022
IEEE Access, 2022
KU X Upstage's Submission for the WMT22 Quality Estimation: Critical Error Detection Shared Task.
Proceedings of the Seventh Conference on Machine Translation, 2022
A Dog Is Passing Over The Jet? A Text-Generation Dataset for Korean Commonsense Reasoning and Evaluation.
Proceedings of the Findings of the Association for Computational Linguistics: NAACL 2022, 2022
Proceedings of the Thirteenth Language Resources and Evaluation Conference, 2022
Empirical Analysis of Noising Scheme based Synthetic Data Generation for Automatic Post-editing.
Proceedings of the Thirteenth Language Resources and Evaluation Conference, 2022
QUAK: A Synthetic Quality Estimation Dataset for Korean-English Neural Machine Translation.
Proceedings of the 29th International Conference on Computational Linguistics, 2022
2021
How should human translation coexist with NMT? Efficient tool for building high quality parallel corpus.
CoRR, 2021
Empirical Analysis of Korean Public AI Hub Parallel Corpora and in-depth Analysis using LIWC.
CoRR, 2021
IEEE Access, 2021
Should we find another model?: Improving Neural Machine Translation Performance with ONE-Piece Tokenization Method without Model Modification.
Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies: Industry Papers, 2021
BTS: Back TranScription for Speech-to-Text Post-Processor using Text-to-Speech-to-Text.
Proceedings of the 8th Workshop on Asian Translation, 2021