Papers by Seokjin Oh
Beyond Reference: Evaluating High Quality Translations Better than Human References (2024.emnlp-main)
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| Challenge: | Existing machine translation metrics give maximum score to reference sentence . however, these metrics overlook the possibility that candidate sentences outperform reference sentences in terms of quality. |
| Approach: | They propose a machine translation metrics that give an absolute score to a translated sentence based on the similarity with the reference sentence. |
| Outcome: | The proposed measure outperforms existing MT metrics in terms of quality and assigns positive scores to candidates that outperformed reference sentences. |
Enhancing Low-resource Fine-grained Named Entity Recognition by Leveraging Coarse-grained Datasets (2023.emnlp-main)
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| Challenge: | Named Entity Recognition (NER) often suffers from insufficient labeled data when the number of annotations exceeds several tens of labels. |
| Approach: | They propose a model with a fine-to- coarse mapping matrix to leverage hierarchical structure explicitly. |
| Outcome: | The proposed model outperforms both K-shot learning and supervised learning methods when dealing with a small number of fine-grained annotations. |