Papers by Jaimeen Ahn
KOLD: Korean Offensive Language Dataset (2022.emnlp-main)
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| Challenge: | Recent directions for offensive language detection focus on English and do not transfer well to other languages because of cultural and linguistic differences. |
| Approach: | They present a Korean offensive language dataset annotated with offensive language comments . they use the comments as training data for Korean BERT and RoBERTa models . |
| Outcome: | The proposed model improves offensiveness detection, target classification, and span detection while having room for improvement for target group classification and span prediction. |
Suicidal Risk Detection for Military Personnel (2020.emnlp-main)
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| Challenge: | a dataset of 2,791 posts with 13,955 expert annotations of suicidal risk levels is available for research . Suicide is one of the major causes of death in the military. |
| Approach: | They analyze posts related to military service in the Republic of Korea and annotate them with military experts and mental health experts. |
| Outcome: | The proposed method predicts the level of suicide risk, reaching .88 F1 for classifying the risks. |
Mitigating Language-Dependent Ethnic Bias in BERT (2021.emnlp-main)
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| Challenge: | Ethnic bias is one of the most prevalent social stereotypes. |
| Approach: | They propose to use a multilingual model and contextual word alignment to mitigate ethnic bias in monolingual BERT for English, German, Spanish, Korean, Turkish, and Chinese. |
| Outcome: | The proposed methods alleviate ethnic bias in English, German, Spanish, Korean, Turkish, and Chinese using a multilingual model and contextual word alignment of two monolingual models. |