Papers by Sungeun Hahm

2 papers
Thunder-DeID: Accurate and Efficient De-identification Framework for Korean Court Judgments (2025.findings-emnlp)

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Challenge: a recent study shows that the current de-identification process is inadequate for court judgments at scale .
Approach: They propose a framework for de-identification that aligns with relevant laws and practices . they construct and release the first Korean legal dataset containing annotated judgments .
Outcome: The proposed framework achieves state-of-the-art in the de-identification of court judgments.
Generalizing Clinical De-identification Models by Privacy-safe Data Augmentation using GPT-4 (2024.emnlp-main)

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Challenge: De-identification (de-ID) is critical for patient confidentiality in clinical data management due to the difficulty of retaining training corpora and labeling standards vary across institutions.
Approach: They propose to exploit GPT-4 for data augmentation through one-shot and zero-shot prompts to exploit the problem of PHI leakage by redacting PHI before processing.
Outcome: The proposed approach significantly improves on three types of F1 scores in cross-dataset testing.

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