Papers by Yerang Kim

1 papers
K/DA: Automated Data Generation Pipeline for Detoxifying Implicitly Offensive Language in Korean (2025.acl-long)

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Challenge: Language detoxification involves removing toxicity from offensive language.
Approach: They propose an automated pipeline to generate offensive language with implicit offensiveness and trend-aligned slang.
Outcome: The proposed dataset exhibits high pair consistency and greater implicit offensiveness compared to existing Korean datasets and demonstrates applicability to other languages.

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