Papers by Jaewon Lee
“Why do I feel offended?” - Korean Dataset for Offensive Language Identification (2023.findings-eacl)
Copied to clipboard
| Challenge: | Existing methods for detecting offensive content rely on labeled datasets, but few consider low-resource languages with relatively less data available for training. |
| Approach: | They propose to use Korean as a dataset for offensive language identification . they propose to perform abusive language detection and sentiment analysis to help identify offensive languages. |
| Outcome: | The proposed datasets improve the performance of offensive language identification in Korean, while the existing methods are limited. |
Captioning for Text-Video Retrieval via Dual-Group Direct Preference Optimization (2025.findings-emnlp)
Copied to clipboard
| Challenge: | auxiliary captions are generic and indistinguishable across visually similar videos . conventional captioning approaches are evaluated using language relevance scores . |
| Approach: | They propose a retrieval framework that directly optimizes caption generation using retrieval relevance scores. |
| Outcome: | The proposed retrieval framework optimizes caption generation using retrieval relevance scores . dual-group direct preference optimization is a learning strategy that supervises captioning . |