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Do-Kyung Kim

2 accepted papers

2025

Analyzing Offensive Language Dataset Insights from Training Dynamics and Human Agreement Level

COLING 2025main

Implicit hate speech detection is challenging due to its subjectivity and context dependence, with existing models often struggling in outof-domain scenarios. We propose CONELA, a novel data refinement strategy that enhances model performance and generalization by integrating human annotation agreem…

Cited by 0SourcePDFScholar
2025

KatFishNet: Detecting LLM-Generated Korean Text through Linguistic Feature Analysis

ACL 2025long

The rapid advancement of large language models (LLMs) increases the difficulty of distinguishing between human-written and LLM-generated text. Detecting LLM-generated text is crucial for upholding academic integrity, preventing plagiarism, protecting copyrights, and ensuring ethical research practic…