Papers by Jiseung Hong
Korean Bio-Medical Corpus (KBMC) for Medical Named Entity Recognition (2024.lrec-main)
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Sungjoo Byun, Jiseung Hong, Sumin Park, Dongjun Jang, Jean Seo, Minseok Kim, Chaeyoung Oh, Hyopil Shin
| Challenge: | Named Entity Recognition (NER) plays a pivotal role in medical Natural Language Processing (NLP) yet, there is no open-source medical NER dataset specifically for Korean. |
| Approach: | They used ChatGPT to construct an open-source Korean NER dataset . they found 20% increase in medical NER performance compared to general Korean ner datasets. |
| Outcome: | The KBMC dataset shows an impressive 20% increase in medical NER performance compared to models trained on general Korean NER datasets. |
Measuring Sycophancy of Language Models in Multi-turn Dialogues (2025.findings-emnlp)
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| Challenge: | Prior research on sycophancy has focused on single-turn factual correctness, overlooking the dynamics of real-world interactions. |
| Approach: | They propose a new evaluation suite that assesses sycophantic behavior in multi-turn, free-form conversational settings. |
| Outcome: | The proposed evaluation suite measures how quickly a model conforms to the user and how frequently it shifts its stance under sustained user pressure. |