Papers by Jiyoung Kim
Specializing Multi-domain NMT via Penalizing Low Mutual Information (2022.emnlp-main)
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| Challenge: | Multi-domain Neural Machine Translation (NMT) trains a single model with multiple domains. |
| Approach: | They propose a method that penalizes low MI to be higher for domain-specific NMTs. |
| Outcome: | The proposed method achieves state-of-the-art performance among current models . it also promotes low MI to be higher resulting in domain-specialized multi-domain NMT. |
KorNAT: LLM Alignment Benchmark for Korean Social Values and Common Knowledge (2024.findings-acl)
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| Challenge: | Large Language Models (LLMs) must possess an understanding of the nation’s culture and basic knowledge. |
| Approach: | They propose to construct a national alignment benchmark, KorNAT, which measures the alignment between an LLM and a targeted country from two perspectives: social value alignment and common knowledge alignment. |
| Outcome: | The proposed model passes the national alignment score of 7 LLMs, indicating there is room for improvement. |
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. |