論文

• Moon Sangwhan, Naoaki Okazaki. The Effects and Mitigation of Out-of-Vocabulary in Universal Language Models. Journal of Information Processing, Journal of Information Processing, Vol. 29, pp. 490-503, July 2021.

国際会議発表 (査読有り)

• Marco Cognetta, Sangwhan Moon, Lawrence Wolf-Sonkin, Naoaki Okazaki. Parameter-Efficient Korean Character-Level Language Modeling, Proceedings of the 17th Conference of the European Chapter of the Association for Computational Linguistics: Main Volume (EACL), pp. 2350-2356, May 2023.
• May Kristine Jonson Carlon, Sangwhan Moon, Naoaki Okazaki, Jeffrey S. Cross. Predicting Guesses and Slips Through Question Encoding with Complexity Hints, IEEE International Conference on Teaching, Assessment, and Learning for Engineering (TALE) 2022, Dec. 2022.
• Moon Sangwhan, Won Ik Cho, Hye Joo Han, Naoaki Okazaki, Nam Soo Kim. OpenKorPOS: Democratizing Korean Tokenization with Voting-Based Open Corpus Annotation, Proceedings of the 13th Language Resources and Evaluation Conference (LREC), June 2022.
• Hwichan Kim, Moon Sangwhan, Naoaki Okazaki, Mamoru Komachi. Learning How to Translate North Korean through South Korean, Proceedings of the 13th Language Resources and Evaluation Conference (LREC), June 2022.
• Moon Sangwhan, Naoaki Okazaki. PatchBERT: Just-in-Time, Out-of-Vocabulary Patching, Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP 2020), Nov. 2020.
• Sangwhan Moon, Naoaki Okazaki. Jamo Pair Encoding, Proceedings of the 12th Conference on Language Resources and Evaluation (LREC 2020), pp. 3490-3497, May 2020.

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